Tue, 20 Aug 2019

Package visualR updated to version 2.0.2 with previous version 2.0.1 dated 2019-05-05

Title: 3D Visualization of Option Greeks and Volatility Skew
Description: Generates a 3D graph which plots the volatility skew of a stock or a selected stock option parameter over time. The default setting plots the net parameter position of a double vertical spread over time.
Author: John T. Buynak
Maintainer: John T. Buynak <jbuynak94@gmail.com>

Diff between visualR versions 2.0.1 dated 2019-05-05 and 2.0.2 dated 2019-08-20

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Package scoringRules updated to version 1.0.0 with previous version 0.9.6 dated 2019-05-27

Title: Scoring Rules for Parametric and Simulated Distribution Forecasts
Description: Dictionary-like reference for computing scoring rules in a wide range of situations. Covers both parametric forecast distributions (such as mixtures of Gaussians) and distributions generated via simulation.
Author: Alexander Jordan, Fabian Krueger, Sebastian Lerch
Maintainer: Fabian Krueger <Fabian.Krueger83@gmail.com>

Diff between scoringRules versions 0.9.6 dated 2019-05-27 and 1.0.0 dated 2019-08-20

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Package clustrd updated to version 1.3.4 with previous version 1.3.2 dated 2019-07-11

Title: Methods for Joint Dimension Reduction and Clustering
Description: A class of methods that combine dimension reduction and clustering of continuous, categorical or mixed-type data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll 1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013, <DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2017; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means. For mixed-type data, it provides mixed Reduced K-means and mixed Factorial K-means (van de Velden, Iodice D'Enza and Markos 2019; <DOI:10.1002/wics.1456>), which combine PCA for mixed-type data with K-means.
Author: Angelos Markos [aut, cre], Alfonso Iodice D'Enza [aut], Michel van de Velden [ctb]
Maintainer: Angelos Markos <amarkos@gmail.com>

Diff between clustrd versions 1.3.2 dated 2019-07-11 and 1.3.4 dated 2019-08-20

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Package xlink updated to version 1.0.1 with previous version 1.0.0 dated 2019-07-03

Title: Genetic Association Models for X-Chromosome SNPS on Continuous, Binary and Survival Outcomes
Description: The expression of X-chromosome undergoes three possible biological processes: X-chromosome inactivation (XCI), escape of the X-chromosome inactivation (XCI-E),and skewed X-chromosome inactivation (XCI-S). To analyze the X-linked genetic association for phenotype such as continuous, binary, and time-to-event outcomes with the actual process unknown, we propose a unified approach of maximizing the likelihood or partial likelihood over all of the potential biological processes. The methods are described in Wei Xu, Meiling Hao (2017) <doi:10.1002/gepi.22097>. And also see Dongxiao Han, Meiling Hao, Lianqiang Qu, Wei Xu (2019) <doi:10.1177/0962280219859037>.
Author: Wei Xu [aut], Meiling Hao [aut], Yi Zhu [cre]
Maintainer: Yi Zhu <yizhu87@gmail.com>

Diff between xlink versions 1.0.0 dated 2019-07-03 and 1.0.1 dated 2019-08-20

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Package Seurat updated to version 3.1.0 with previous version 3.0.2 dated 2019-06-14

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Butler A and Satija R (2017) <doi:10.1101/164889> for more details.
Author: Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb], Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>)
Maintainer: Paul Hoffman <nygcSatijalab@nygenome.org>

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Package orthoDr updated to version 0.6.2 with previous version 0.5 dated 2018-03-25

Title: Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization
Description: Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2017) <arXiv:1704.05046> and Zhou & Zhu (2018+) <arXiv:1802.06156>. It also serves as a general purpose optimization solver for problems with orthogonality constraints. Parallel computing for approximating the gradient is enabled through `OpenMP'.
Author: Ruilin Zhao, Ruoqing Zhu, Jiyang Zhang, Wenzhuo Zhou and Peng Xu
Maintainer: Ruoqing Zhu <teazrq@gmail.com>

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Package kernscr updated to version 1.0.5 with previous version 1.0.3 dated 2016-06-28

Title: Kernel Machine Score Test for Semi-Competing Risks
Description: Kernel Machine Score Test for Pathway Analysis in the Presence of Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) <doi: 10.1177/0962280216653427>.
Author: Matey Neykov [aut], Boris P Hejblum [aut, cre], Jennifer A Sinnot [aut]
Maintainer: Boris P Hejblum <boris.hejblum@u-bordeaux.fr>

Diff between kernscr versions 1.0.3 dated 2016-06-28 and 1.0.5 dated 2019-08-20

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Package gtsummary updated to version 1.2.1 with previous version 1.2.0 dated 2019-08-19

Title: Presentation-Ready Data Summary and Analytic Result Tables
Description: Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers. The package is enhanced when the 'gt' package is installed. Use this code to install: 'remotes::install_github("rstudio/gt")'.
Author: Daniel D. Sjoberg [aut, cre] (<https://orcid.org/0000-0003-0862-2018>), Margie Hannum [aut] (<https://orcid.org/0000-0002-2953-0449>), Karissa Whiting [aut] (<https://orcid.org/0000-0002-4683-1868>), Emily C. Zabor [aut] (<https://orcid.org/0000-0002-1402-4498>), Michael Curry [ctb] (<https://orcid.org/0000-0002-0261-4044>), Esther Drill [ctb] (<https://orcid.org/0000-0002-3315-4538>), Jessica Flynn [ctb] (<https://orcid.org/0000-0001-8310-6684>)
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

Diff between gtsummary versions 1.2.0 dated 2019-08-19 and 1.2.1 dated 2019-08-20

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Package dlsem updated to version 2.4.3 with previous version 2.4.2 dated 2019-05-27

Title: Distributed-Lag Linear Structural Equation Models
Description: Inference functionalities for distributed-lag linear structural equation models (DLSEMs). DLSEMs are Markovian structural causal models where each factor of the joint probability distribution is a distributed-lag linear regression (Magrini, 2018 <doi:10.2478/bile-2018-0012>; Magrini et al., 2019 <doi:10.1007/s11135-019-00855-z>). DLSEMs account for temporal delays in the dependence relationships among the variables and allow to perform dynamic causal inference by assessing causal effects at different time lags. Endpoint-constrained quadratic, quadratic decreasing and gamma lag shapes are available.
Author: Alessandro Magrini
Maintainer: Alessandro Magrini <alessandro.magrini@unifi.it>

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Package bestNormalize updated to version 1.4.2 with previous version 1.4.0 dated 2019-05-13

Title: Normalizing Transformation Functions
Description: Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation. It also estimates the normalization efficacy of other commonly used transformations.
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan.a.peterson@cuanschutz.edu>

Diff between bestNormalize versions 1.4.0 dated 2019-05-13 and 1.4.2 dated 2019-08-20

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Package BallMapper updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-26

Title: The Ball Mapper Algorithm
Description: The core algorithm is described in "Ball mapper: a shape summary for topological data analysis" by Pawel Dlotko, (2019) <arXiv:1901.07410>. Please consult the following youtube video <https://www.youtube.com/watch?v=M9Dm1nl_zSQfor> the idea of functionality. Ball Mapper provide a topologically accurate summary of a data in a form of an abstract graph. To create it, please provide the coordinates of points (in the points array), values of a function of interest at those points (can be initialized randomly if you do not have it) and the value epsilon which is the radius of the ball in the Ball Mapper construction. It can be understood as the minimal resolution on which we use to create the model of the data.
Author: Pawel Dlotko [aut, cre]
Maintainer: Pawel Dlotko <pdlotko@gmail.com>

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Package vcr updated to version 0.3.0 with previous version 0.2.6 dated 2019-02-12

Title: Record 'HTTP' Calls to Disk
Description: Record test suite 'HTTP' requests and replays them during future runs. A port of the Ruby gem of the same name (<https://github.com/vcr/vcr/>). Works by hooking into the 'webmockr' R package for matching 'HTTP' requests by various rules ('HTTP' method, 'URL', query parameters, headers, body, etc.), and then caching real 'HTTP' responses on disk in 'cassettes'. Subsequent 'HTTP' requests matching any previous requests in the same 'cassette' use a cached 'HTTP' response.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <sckott@protonmail.com>

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Package MazamaCoreUtils updated to version 0.3.1 with previous version 0.2.0 dated 2019-07-18

Title: Utility Functions for Production R Code
Description: A suite of utility functions providing functionality commonly needed for production level projects such as logging, error handling, and cache management.
Author: Jonathan Callahan [aut, cre], Spencer Pease [aut], Thomas Bergamaschi [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package RCzechia updated to version 1.4.2 with previous version 1.4.1 dated 2019-07-01

Title: Spatial Objects of the Czech Republic
Description: Administrative regions and other spatial objects of the Czech Republic.
Author: Jindra Lacko
Maintainer: Jindra Lacko <jindra.lacko@gmail.com>

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Package GENEAread updated to version 2.0.7 with previous version 2.0.6 dated 2018-11-16

Title: Package for Reading Binary Files
Description: Functions and analytics for GENEA-compatible accelerometer data into R objects. See topic 'GENEAread' for an introduction to the package.
Author: Zhou Fang [aut], Joss Langford [aut], Charles Sweetland [aut, cre]
Maintainer: Charles Sweetland <charles@sweetland-solutions.co.uk>

Diff between GENEAread versions 2.0.6 dated 2018-11-16 and 2.0.7 dated 2019-08-20

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New package lactcurves with initial version 1.0.0
Package: lactcurves
Type: Package
Title: Lactation Curve Parameter Estimation
Version: 1.0.0
Author: Eva M. Strucken
Maintainer: Eva M. Strucken <estrucke@une.edu.au>
Description: AllCurves() runs multiple lactation curve models and extracts selection criteria for each model. This package summarises the most common lactation curve models from the last century and provides a tool for researchers to quickly decide on which model fits their data best to proceed with their analysis. Start parameters were optimized based on a dataset with 1.7 million Holstein-Friesian cows. If convergence fails, the start parameters need to be manually adjusted. The models included in the package are taken from: (1) Michaelis-Menten: Michaelis, L. and M.L. Menten (1913). <www.plantphys.info/plant_physiology/copyright/MichaelisMentenTranslation2.pdf> (1a) Michaelis-Menten (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). <doi:10.1017/S002185960007684X> (1b) Michaelis-Menten + exponential (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). <doi:10.1017/S002185960007684X> (2) Brody (1923): Brody, S., A.C. Ragsdale, and C.W. Turner (1923). <doi:10.1085/jgp.5.6.777> (3) Brody (1924): Brody, S., C.W. Tuner, and A.C. Ragsdale (1924). <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2140670/> (4) Schumacher: Schumacher, F.X. (1939) in Thornley, J.H.M. and J. France (2007). <https://books.google.com.au/books/about/Mathematical_Models_in_Agriculture.html?id=rlwBCRSHobcC&redir_esc=y> (4a) Schumacher (Lopez et al. 2015): Lopez, S. J. France, N.E. Odongo, R.A. McBride, E. Kebreab, O. AlZahal, B.W. McBride, and J. Dijkstra (2015). <doi:10.3168/jds.2014-8132> (5) Parabolic exponential (Adediran): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (6) Wood: Wood, P.D.P. (1967). <doi:10.1038/216164a0> (6a) Wood reparameterized (Dhanoa): Dhanoa, M.S. (1981). <doi:10.1017/S0003356100027276> (6b) Wood non-linear (Cappio-Borlino): Cappio-Borlino, A., G. Pulina, and G. Rossi (1995). <doi:10.1016/0921-4488(95)00713-U> (7) Quadratic Polynomial (Dave): Dave, B.K. (1971) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (8) Cobby and Le Du (Vargas): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). <doi:10.3168/jds.S0022-0302(00)75005-3> (9) Papajcsik and Bodero 1: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (10) Papajcsik and Bodero 2: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (11) Papajcsik and Bodero 3: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (12) Papajcsik and Bodero 4: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (13) Papajcsik and Bodero 6: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (14) Mixed log model 1 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (15) Mixed log model 3 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (16) Log-quadratic (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (17) Wilmink: J.B.M. Wilmink (1987). <doi:10.1016/0301-6226(87)90003-0> (17a) modified Wilmink (Jakobsen): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (17b) modified Wilmink (Laurenson & Strucken): in preparation (2019). (18) Bicompartemental (Ferguson and Boston 1993): Ferguson, J.D., and R. Boston (1993) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (19) Dijkstra: Dijkstra, J., J. France, M.S. Dhanoa, J.A. Maas, M.D. Hanigan, A.J. Rook, and D.E. Beever (1997). <doi10.3168/jds.S0022-0302(97)76185-X> (20) Morant and Gnanasakthy (Pollott et al 2000): Pollott, G.E. and E. Gootwine (2000). <doi10.1017/S1357729800055028> (21) Morant and Gnanasakthy (Vargas et al 2000): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). <doi:10.3168/jds.S0022-0302(00)75005-3> (22) Morant and Gnanasakthy (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (23) Khandekar (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (24) Ali and Schaeffer: Ali, T.E. and L.R. Schaeffer (1987). <https://www.nrcresearchpress.com/doi/pdf/10.4141/cjas87-067> (25) Fractional Polynomial (Elvira et al. 2013): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). <doi:10.1017/S175173111200239X> (26) Pollott multiplicative (Elvira): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). <doi:10.1017/S175173111200239X> (27) Pollott modified: Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (28) Monophasic Grossman: Grossman, M. and W.J. Koops (1988). <doi:10.3168/jds.S0022-0302(88)79723-4> (29) Monophasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (30) Diphasic (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (31) Diphasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (32) Legendre Polynomial (3th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (33) Legendre Polynomial (4th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (34) Legendre + Wilmink (Lidauer): Lidauer, M. and E.A. Mantysaari (1999). <https://journal.interbull.org/index.php/ib/article/view/417> (35) Natural Cubic Spline (3 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). <doi:10.3168/jds.S0022-0302(99)75277-X> (36) Natural Cubic Spline (4 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). <doi:10.3168/jds.S0022-0302(99)75277-X> (37) Natural Cubic Spline (5 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999) <doi:10.3168/jds.S0022-0302(99)75277-X> (38) Natural Cubic Spline (defined knots according to Harrell 2001): Jr. Harrell, F.E. (2001). <https://link.springer.com/book/10.1007/978-3-319-19425-7> The selection criteria measure the goodness of fit of the model and include: Residual standard error (RSE), R-square (R2), log likelihood, Akaike information criterion (AIC), Akaike information criterion corrected (AICC), Bayesian Information Criterion (BIC), Durbin Watson coefficient (DW). The following model parameters are included: Residual sum of squares (RSS), Residual standard deviation (RSD), F-value (F) based on F-ratio test.
License: GPL-3
Depends: orthopolynom,splines
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-20 05:10:34 UTC; estrucke
Repository: CRAN
Date/Publication: 2019-08-20 16:30:02 UTC

More information about lactcurves at CRAN
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Package blackbox updated to version 1.1.27 with previous version 1.1.25 dated 2018-06-08

Title: Black Box Optimization and Exploration of Parameter Space
Description: Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Raphaël Leblois [ctb] (<https://orcid.org/0000-0002-3051-4497>)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

Diff between blackbox versions 1.1.25 dated 2018-06-08 and 1.1.27 dated 2019-08-20

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 R/blackbox.R                                                                         |    4 
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 inst/NEWS.Rd                                                                         |   10 
 tests/test-all.R                                                                     |    2 
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New package spread with initial version 2019.8.5
Package: spread
Title: Infectious Disease Spread Models
Version: 2019.8.5
Authors@R: c( person("Solveig", "Engebretsen", email = "solveig.engebretsen@medisin.uio.no", role = c("aut")), person("Andreas Nygård", "Osnes", email = "andreas.n.osnes@gmail.com", role = c("aut")), person("Richard", "White", email = "w@rwhite.no", role = c("aut", "cre")))
Description: A stochastic SEIIaR (susceptible, exposed, infectious, infectious asymptomatic, recovered) metapopulation model that including commuting. Each location has a local infection system, while the locations are connected by people who commute each day. The model differentiates between day and night. During the day you can infect/be infected in the location where you work, while during the night you can infect/be infected in the location where you live. It is the same commuters who travel back and forth each day. At the start of a day, all commuters are sent to their work location, where they mix for 12 hours. The commuters are then sent to their respective home locations, where they mix for 12 hours. The model is loosely based upon a published model by Engebretsen (2019) <doi:10.1371/journal.pcbi.1006879>.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.9.4), RcppProgress (>= 0.1), data.table, fhidata, stringr, readxl, zoo
Suggests: testthat, knitr, ggplot2, glue, rmarkdown
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppProgress
VignetteBuilder: knitr
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-08-20 06:47:56 UTC; rstudio
Author: Solveig Engebretsen [aut], Andreas Nygård Osnes [aut], Richard White [aut, cre]
Maintainer: Richard White <w@rwhite.no>
Repository: CRAN
Date/Publication: 2019-08-20 15:50:02 UTC

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New package pass.lme with initial version 0.9.0
Package: pass.lme
Type: Package
Title: Power and Sample Size for Linear Mixed Effect Models
Version: 0.9.0
Depends: R (>= 3.2.5)
Author: Marco Chak Yan YU
Maintainer: Marco Chak Yan YU <marcocyyu@gmail.com>
Description: Power and sample size calculation for testing fixed effect coefficients in multilevel linear mixed effect models with one or more than one independent populations. Laird, Nan M. and Ware, James H. (1982) <doi:10.2307/2529876>.
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-20 08:34:36 UTC; marco
Repository: CRAN
Date/Publication: 2019-08-20 15:50:05 UTC

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Package overlapping updated to version 1.5.4 with previous version 1.5.3 dated 2019-05-28

Title: Estimation of Overlapping in Empirical Distributions
Description: Functions for estimating the overlapping area of two or more kernel density estimations from empirical data.
Author: Massimiliano Pastore
Maintainer: Massimiliano Pastore <massimiliano.pastore@unipd.it>

Diff between overlapping versions 1.5.3 dated 2019-05-28 and 1.5.4 dated 2019-08-20

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Package mDAG updated to version 1.2.2 with previous version 1.2 dated 2019-03-13

Title: Inferring Causal Network from Mixed Observational Data Using a Directed Acyclic Graph
Description: Learning a mixed directed acyclic graph based on both continuous and categorical data.
Author: Wujuan Zhong, Li Dong, Quefeng Li, Xiaojing Zheng
Maintainer: Wujuan Zhong <zhongwujuan@gmail.com>

Diff between mDAG versions 1.2 dated 2019-03-13 and 1.2.2 dated 2019-08-20

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Package lgr updated to version 0.3.2 with previous version 0.3.1 dated 2019-06-13

Title: A Fully Featured Logging Framework
Description: A flexible, feature-rich yet light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, 'JSON', (rotating) files, memory buffers, and databases, as well as email and push notifications. For a full list of features with examples please refer to the package vignette.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between lgr versions 0.3.1 dated 2019-06-13 and 0.3.2 dated 2019-08-20

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New package implicitMeasures with initial version 0.1.0
Package: implicitMeasures
Type: Package
Title: Computes the Scores for Different Implicit Measures
Version: 0.1.0
Author: Ottavia M. Epifania [aut, cre], Pasquale Anselmi [ctb], Egidio Robusto [ctb]
Maintainer: Ottavia M. Epifania <otta.epifania@gmail.com>
Description: A tool for computing the scores for the Implicit Association Test (IAT; Greenwald, McGhee & Schwartz (1998) <doi:10.1037/0022-3514.74.6.1464>) and the Single Category-IAT (SC-IAT: Karpinski & Steinman (2006) <doi:10.1037/0022-3514.91.1.16>). Functions for preparing the data (both for the IAT and the SC-IAT), plotting the results, and obtaining a table with the scores of implicit measures descriptive statistics are provided.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, ggplot2, methods, plyr, qpdf, tidyr, xtable
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, tableHTML, data.table
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 11:46:22 UTC; huawei
Repository: CRAN
Date/Publication: 2019-08-20 15:40:05 UTC

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Package bioacoustics updated to version 0.2.1 with previous version 0.2.0.1 dated 2019-06-09

Title: Analyse Audio Recordings and Automatically Extract Animal Vocalizations
Description: Contains all the necessary tools to process audio recordings of various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, display audio signals, detect and extract automatically acoustic features for further analysis such as classification.
Author: Jean Marchal [aut, cre], Francois Fabianek [aut], Christopher Scott [aut], Chris Corben [ctb, cph] (Read ZC files, original C code), David Riggs [ctb, cph] (Read GUANO metadata, original R code), Peter Wilson [ctb, cph] (Read ZC files, original R code), Wildlife Acoustics, inc. [ctb, cph] (Read WAC files, original C code), WavX, inc. [cph]
Maintainer: Jean Marchal <jean.marchal@wavx.ca>

Diff between bioacoustics versions 0.2.0.1 dated 2019-06-09 and 0.2.1 dated 2019-08-20

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Package ssizeRNA updated to version 1.3.2 with previous version 1.3.1 dated 2019-02-19

Title: Sample Size Calculation for RNA-Seq Experimental Design
Description: We propose a procedure for sample size calculation while controlling false discovery rate for RNA-seq experimental design. Our procedure depends on the Voom method proposed for RNA-seq data analysis by Law et al. (2014) <DOI:10.1186/gb-2014-15-2-r29> and the sample size calculation method proposed for microarray experiments by Liu and Hwang (2007) <DOI:10.1093/bioinformatics/btl664>. We develop a set of functions that calculates appropriate sample sizes for two-sample t-test for RNA-seq experiments with fixed or varied set of parameters. The outputs also contain a plot of power versus sample size, a table of power at different sample sizes, and a table of critical test values at different sample sizes. To install this package, please use 'source("http://bioconductor.org/biocLite.R"); biocLite("ssizeRNA")'. For R version 3.5 or greater, please use 'if(!requireNamespace("BiocManager", quietly = TRUE)){install.packages("BiocManager")}; BiocManager::install("ssizeRNA")'.
Author: Ran Bi [aut, cre], Peng Liu [aut], Tim Triche [ctb]
Maintainer: Ran Bi <biranpier@gmail.com>

Diff between ssizeRNA versions 1.3.1 dated 2019-02-19 and 1.3.2 dated 2019-08-20

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New package electivity with initial version 1.0.2
Package: electivity
Type: Package
Title: Algorithms for Electivity Indices
Version: 1.0.2
Date: 2019-08-13
Authors@R: person("Desi", "Quintans", email = "science@desiquintans.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3356-0293"))
Description: Provides all electivity algorithms (including Vanderploeg and Scavia electivity) that were examined in Lechowicz (1982) <doi:10.1007/BF00349007>, plus the example data that were provided for moth resource utilisation.
URL: https://github.com/DesiQuintans/electivity
BugReports: https://github.com/DesiQuintans/electivity/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Suggests: utils (>= 3.4.2), usethis (>= 1.0.0)
RoxygenNote: 6.1.1
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2019-08-19 21:38:27 UTC; 90928711
Author: Desi Quintans [aut, cre] (<https://orcid.org/0000-0003-3356-0293>)
Maintainer: Desi Quintans <science@desiquintans.com>
Repository: CRAN
Date/Publication: 2019-08-20 14:50:05 UTC

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Package comorbidity updated to version 0.5.0 with previous version 0.4.1 dated 2019-06-27

Title: Computing Comorbidity Scores
Description: Computing comorbidity scores such as the weighted Charlson score (Charlson, 1987 <doi:10.1016/0021-9681(87)90171-8>) and the Elixhauser comorbidity score (Elixhauser, 1998 <doi:10.1097/00005650-199801000-00004>) using ICD-9-CM or ICD-10 codes (Quan, 2005 <doi:10.1097/01.mlr.0000182534.19832.83>).
Author: Alessandro Gasparini [aut, cre] (<https://orcid.org/0000-0002-8319-7624>), Hojjat Salmasian [ctb] (ICD-9-CM scores), Jonathan Williman [ctb] (<https://orcid.org/0000-0001-5080-4435>)
Maintainer: Alessandro Gasparini <ag475@leicester.ac.uk>

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Package sugarbag updated to version 0.1.1 with previous version 0.1.0 dated 2019-06-14

Title: Create Tessellated Hexagon Maps
Description: Create a hexagon tilegram from spatial polygons. Each polygon is represented by a hexagon tile, placed as close to it's original centroid as possible, with a focus on maintaining spatial relationship to a focal point. Developed to aid visualisation and analysis of spatial distributions across Australia, which can be challenging due to the concentration of the population on the coast and wide open interior.
Author: Stephanie Kobakian [aut, cre], Dianne Cook [aut, ths]
Maintainer: Stephanie Kobakian <stephanie.kobakian@gmail.com>

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Package suddengains updated to version 0.3.0 with previous version 0.2.1 dated 2019-05-21

Title: Identify Sudden Gains in Longitudinal Data
Description: Identify sudden gains based on the three criteria outlined by Tang and DeRubeis (1999) <doi:10.1037/0022-006X.67.6.894> to a selection of repeated measures. Sudden losses, defined as the opposite of sudden gains can also be identified. Two different datasets can be created, one including all sudden gains/losses and one including one selected sudden gain/loss for each case. It can extract scores around sudden gains/losses. It can plot the average change around sudden gains/losses and trajectories of individual cases.
Author: Milan Wiedemann [aut, cre] (<https://orcid.org/0000-0003-1991-282X>), Graham M Thew [ctb] (<https://orcid.org/0000-0003-2851-1315>), Richard Stott [ctb] (<https://orcid.org/0000-0003-2533-5504>), Anke Ehlers [ctb, ths] (<https://orcid.org/0000-0002-8742-0192>)
Maintainer: Milan Wiedemann <milan.wiedemann@gmail.com>

Diff between suddengains versions 0.2.1 dated 2019-05-21 and 0.3.0 dated 2019-08-20

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Package RgoogleMaps updated to version 1.4.4 with previous version 1.4.3 dated 2018-11-07

Title: Overlays on Static Maps
Description: Serves two purposes: (i) Provide a comfortable R interface to query the Google server for static maps, and (ii) Use the map as a background image to overlay plots within R. This requires proper coordinate scaling.
Author: Markus Loecher
Maintainer: Markus Loecher <markus.loecher@gmail.com>

Diff between RgoogleMaps versions 1.4.3 dated 2018-11-07 and 1.4.4 dated 2019-08-20

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Package highfrequency updated to version 0.6.0 with previous version 0.5.3 dated 2018-03-03

Title: Tools for Highfrequency Data Analysis
Description: Provide functionality to manage, clean and match highfrequency trades and quotes data, calculate various liquidity measures, estimate and forecast volatility, detect price jumps and investigate microstructure noise and intraday periodicity.
Author: Kris Boudt [aut, cre], Jonathan Cornelissen [aut], Scott Payseur [aut], Giang Nguyen [ctb], Onno Kleen [ctb] (<https://orcid.org/0000-0003-4731-4640>)
Maintainer: Kris Boudt <Kris.Boudt@econ.kuleuven.be>

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Package difNLR updated to version 1.3.0 with previous version 1.2.2 dated 2018-05-06

Title: DIF and DDF Detection by Non-Linear Regression Models
Description: Detection of differential item functioning (DIF) among dichotomously scored items and differential distractor functioning (DDF) among unscored items with non-linear regression procedures based on generalized logistic regression models (Drabinova and Martinkova, 2017, doi:10.1111/jedm.12158).
Author: Adela Hladka [aut, cre], Patricia Martinkova [aut], Karel Zvara [ctb]
Maintainer: Adela Hladka <hladka@cs.cas.cz>

Diff between difNLR versions 1.2.2 dated 2018-05-06 and 1.3.0 dated 2019-08-20

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Package cbsodataR updated to version 0.3.4 with previous version 0.3.2 dated 2019-02-21

Title: Statistics Netherlands (CBS) Open Data API Client
Description: The data and meta data from Statistics Netherlands (<https://www.cbs.nl>) can be browsed and downloaded. The client uses the open data API of Statistics Netherlands.
Author: Edwin de Jonge [aut, cre], Sara Houweling [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

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Package semPlot updated to version 1.1.2 with previous version 1.1.1 dated 2019-04-05

Title: Path Diagrams and Visual Analysis of Various SEM Packages' Output
Description: Path diagrams and visual analysis of various SEM packages' output.
Author: Sacha Epskamp [aut, cre], Simon Stuber [ctb], Jason Nak [ctb], Myrthe Veenman [ctb], Terrence D. Jorgensen [ctb] (<https://orcid.org/0000-0001-5111-6773>)
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between semPlot versions 1.1.1 dated 2019-04-05 and 1.1.2 dated 2019-08-20

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Package Peptides updated to version 2.4.1 with previous version 2.4 dated 2018-06-08

Title: Calculate Indices and Theoretical Physicochemical Properties of Protein Sequences
Description: Includes functions to calculate several physicochemical properties and indices for amino-acid sequences as well as to read and plot 'XVG' output files from the 'GROMACS' molecular dynamics package.
Author: Daniel Osorio [aut, cre], Paola Rondon-Villarreal [aut, ths], Rodrigo Torres [aut, ths], J. Sebastian Paez [ctb]
Maintainer: Daniel Osorio <dcosorioh@tamu.edu>

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New package NetSimR with initial version 0.1.0
Package: NetSimR
Type: Package
Title: Actuarial Functions for Non-Life Insurance Modelling
Version: 0.1.0
Author: Yiannis Parizas [aut, cre]
Authors@R: person("Yiannis", "Parizas", email = "yiannis.parizas@gmail.com", role = c("aut", "cre"))
Maintainer: Yiannis Parizas <yiannis.parizas@gmail.com>
Description: Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, crch, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 16:31:54 UTC; yiann
Repository: CRAN
Date/Publication: 2019-08-20 11:30:12 UTC

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New package ihpdr with initial version 1.0.0
Package: ihpdr
Title: Download Data from the International House Price Database
Version: 1.0.0
Authors@R: person(given = "Kostas", family = "Vasilopoulos", role = c("aut", "cre"), email = "k.vasilopoulo@gmail.com")
Description: Web scraping the <https://www.dallasfed.org> for up-to-date data on international house prices and exuberance indicators. Download data in tidy format.
Encoding: UTF-8
LazyData: true
Imports: rvest (>= 0.3.4), xml2 (>= 1.2.0), magrittr (>= 1.5), httr (>= 1.4.0), readxl (>= 1.3.1), dplyr (>= 0.8.3), lubridate (>= 1.7.4), purrr (>= 0.3.2), rlang (>= 0.4.0), tidyr (>= 0.8.3)
RoxygenNote: 6.1.1
URL: https://github.com/kvasilopoulos/ihpdr
BugReports: https://github.com/kvasilopoulos/ihpdr/issues
Suggests: spelling, testthat (>= 2.1.0), covr
Language: en-US
License: GPL-3
NeedsCompilation: no
Packaged: 2019-08-19 16:26:00 UTC; T460p
Author: Kostas Vasilopoulos [aut, cre]
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-20 11:30:06 UTC

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Package hutilscpp updated to version 0.2.0 with previous version 0.1.0 dated 2019-02-03

Title: Miscellaneous Functions in C++
Description: Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

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Package graphlayouts updated to version 0.5.0 with previous version 0.2.0 dated 2019-07-04

Title: Additional Layout Algorithms for Network Visualizations
Description: Several new layout algorithms to visualize networks are provided which are not part of 'igraph'. Most are based on the concept of stress majorization by Gansner et al. (2004) <doi:10.1007/978-3-540-31843-9_25>. Some more specific algorithms allow to emphasize hidden group structures in networks or focus on specific nodes.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>

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Package dtpcrm updated to version 0.1.1 with previous version 0.1.0 dated 2019-04-10

Title: Dose Transition Pathways for Continual Reassessment Method
Description: Provides the dose transition pathways (DTP) to project in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, deescalate or stop early) using all the accumulated toxicity information; See Yap et al (2017) <doi: 10.1158/1078-0432.CCR-17-0582>. DTP can be used as a design and an operational tool and can be displayed as a table or flow diagram. The 'dtpcrm' package also provides the modified continual reassessment method (CRM) and time-to-event CRM (TITE-CRM) with added practical considerations to allow stopping early when there is sufficient evidence that the lowest dose is too toxic and/or there is a sufficient number of patients dosed at the maximum tolerated dose.
Author: Christina Yap [aut, cre], Daniel Slade [aut], Kristian Brock [aut], Yi Pan [aut]
Maintainer: Christina Yap <yapchristina17@gmail.com>

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Package DataVisualizations updated to version 1.1.8 with previous version 1.1.6 dated 2019-03-08

Title: Visualizations of High-Dimensional Data
Description: Gives access to data visualisation methods that are relevant from the data scientist's point of view. The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) for either classified or non-classified multivariate data presented in Thrun et al. (2019) <arXiv:1908.06081>. The MD-plot outperforms the box-and-whisker diagram (box plot) and bean plot. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Felix Pape [aut, rev], Onno Hansen-Goos [ctr, ctb], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package clean updated to version 1.1.0 with previous version 1.0.0 dated 2019-07-28

Title: Fast and Easy Data Cleaning
Description: Data cleaning functions for classes 'logical', 'factor', 'numeric', 'character', 'currency' and 'Date' to make data cleaning fast and easy. Relying on very few dependencies, it provides smart guessing, but with user options to override anything if needed.
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>)
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

Diff between clean versions 1.0.0 dated 2019-07-28 and 1.1.0 dated 2019-08-20

 DESCRIPTION                    |   14 +-
 MD5                            |   21 ++--
 NAMESPACE                      |   36 ++++++
 NEWS.md                        |   11 ++
 R/clean.R                      |   81 ++++++++++++++-
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 R/freq.R                       |  213 +++++++++++++++++++++++------------------
 R/helpers.R                    |   17 ++-
 README.md                      |   74 ++++++++++++--
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 tests/testthat/test-currency.R |only
 13 files changed, 380 insertions(+), 145 deletions(-)

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Package bvartools updated to version 0.0.2 with previous version 0.0.1 dated 2019-06-11

Title: Bayesian Inference of Vector Autoregressive Models
Description: Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2007, ISBN: 9783540262398).
Author: Franz X. Mohr [aut, cre]
Maintainer: Franz X. Mohr <bvartools@outlook.com>

Diff between bvartools versions 0.0.1 dated 2019-06-11 and 0.0.2 dated 2019-08-20

 DESCRIPTION                |   10 ++---
 MD5                        |   69 +++++++++++++++++++++------------------
 NAMESPACE                  |    2 +
 NEWS.md                    |only
 R/RcppExports.R            |   11 ++++--
 R/bvar.R                   |   11 ++++--
 R/bvec_to_bvar.R           |    6 ++-
 R/fevd.R                   |    2 -
 R/gen_var.R                |   41 +++++++++++++++++------
 R/gen_vec.R                |   41 +++++++++++++++++++++--
 R/irf.R                    |    6 ++-
 R/minnesota_prior.R        |only
 R/plot.bvarfevd.R          |    8 +++-
 R/predict.bvar.R           |   38 +++++++++++++++++----
 R/ssvs_prior.R             |only
 build/vignette.rds         |binary
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 vignettes/bsvar.Rmd        |    1 
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 vignettes/bvec.Rmd         |    1 
 vignettes/ssvs.Rmd         |   10 +----
 38 files changed, 309 insertions(+), 186 deletions(-)

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New package tidycells with initial version 0.2.0
Type: Package
Package: tidycells
Title: Read Tabular Data from Diverse Sources and Easily Make Them Tidy
Version: 0.2.0
Authors@R: person(given = "Indranil", family = "Gayen", role = c("aut", "cre"), email = "nil.gayen@gmail.com", comment = c(ORCID = "0000-0003-0197-1944"))
Description: Provides utilities to read, cells from complex tabular data and heuristic detection based 'structural assignment' of those cells to a columnar or tidy format. Read functionality has the ability to read structured, partially structured or unstructured tabular data from various types of documents. The 'structural assignment' functionality has both supervised and unsupervised way of assigning cells data to columnar/tidy format. Multiple disconnected blocks of tables in a single sheet are also handled appropriately. These tools are suitable for unattended conversation of messy tables into a consumable format(usable for further analysis and data wrangling).
License: MIT + file LICENSE
URL: https://r-rudra.github.io/tidycells/, https://github.com/r-rudra/tidycells
BugReports: https://github.com/r-rudra/tidycells/issues
Depends: R (>= 3.2.0)
Imports: dplyr (>= 0.8.1), ggplot2, graphics, magrittr, methods, purrr (>= 0.3.2), rlang, stats, stringr (>= 1.4.0), tibble, tidyr, unpivotr (>= 0.5.1), utils
Suggests: cli, covr, docxtractr, DT, knitr, miniUI, plotly, readr, readxl, rmarkdown, rstudioapi, shiny, shinytest, stringdist, tabulizer, testthat (>= 2.1.0), tidyxl, xlsx, XML
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 13:36:24 UTC; igayen
Author: Indranil Gayen [aut, cre] (<https://orcid.org/0000-0003-0197-1944>)
Maintainer: Indranil Gayen <nil.gayen@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-20 10:30:02 UTC

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Package qrandom updated to version 1.2 with previous version 1.1 dated 2019-02-14

Title: True Random Numbers using the ANU Quantum Random Numbers Server
Description: The ANU Quantum Random Number Generator provided by the Australian National University generates true random numbers in real-time by measuring the quantum fluctuations of the vacuum. This package offers an interface using their API. The electromagnetic field of the vacuum exhibits random fluctuations in phase and amplitude at all frequencies. By carefully measuring these fluctuations, one is able to generate ultra-high bandwidth random numbers. The quantum Random Number Generator is based on the papers by Symul et al., (2011) <doi:10.1063/1.3597793> and Haw, et al. (2015) <doi:10.1103/PhysRevApplied.3.054004>. The package offers functions to retrieve a sequence of random integers or hexadecimals and true random samples from a normal or uniform distribution.
Author: Siegfried Köstlmeier [aut, cre] (<https://orcid.org/0000-0002-7221-6981>), Boris Steipe [ctb] (<https://orcid.org/0000-0002-1134-6758>)
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

Diff between qrandom versions 1.1 dated 2019-02-14 and 1.2 dated 2019-08-20

 DESCRIPTION                         |    9 
 LICENSE                             |  678 ++++++++++++++++++------------------
 MD5                                 |   40 +-
 NAMESPACE                           |   32 -
 R/qUUID.R                           |  152 ++++----
 R/qrandom.R                         |  664 +++++++++++++++++------------------
 R/qrandommaxint.R                   |  118 +++---
 THANKS                              |    7 
 build/partial.rdb                   |binary
 man/qRandomSeq.Rd                   |   54 +-
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 man/qrandomunif.Rd                  |  134 +++----
 tests/testthat.R                    |   20 -
 tests/testthat/test-qUUID.R         |   56 +-
 tests/testthat/test-qrandom.R       |   56 +-
 tests/testthat/test-qrandommaxint.R |   46 +-
 tests/testthat/test-qrandomnorm.R   |   32 -
 tests/testthat/test-qrandomunif.R   |   38 +-
 21 files changed, 1361 insertions(+), 1355 deletions(-)

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Package metadynminer updated to version 0.1.6 with previous version 0.1.5 dated 2019-07-18

Title: Tools to Read, Analyze and Visualize Metadynamics HILLS Files from 'Plumed'
Description: Metadynamics is a state of the art biomolecular simulation technique. 'Plumed' Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Transition states can be analyzed by Nudged Elastic Band method by Henkelman, G. and Jonsson, H. (2000) <doi:10.1063/1.1323224>. Free energy surfaces, minima and transition paths can be plotted to produce publication quality images.
Author: Vojtech Spiwok [aut, cre] (<https://orcid.org/0000-0001-8108-2033>)
Maintainer: Vojtech Spiwok <spiwokv@vscht.cz>

Diff between metadynminer versions 0.1.5 dated 2019-07-18 and 0.1.6 dated 2019-08-20

 DESCRIPTION        |    8 +++----
 MD5                |   11 +++++-----
 NAMESPACE          |    1 
 R/minimaandpaths.R |   12 +++++++++--
 R/nebs.R           |    4 +++
 R/readingandfes.R  |   54 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 man/prob.Rd        |only
 7 files changed, 79 insertions(+), 11 deletions(-)

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Package HiCblock updated to version 1.5 with previous version 1.4 dated 2018-04-18

Title: Systematic Analysis of Architectural Proteins and Functional Elements in Blocking Long-Range Contacts Between Loci
Description: Here we propose a model to systematically analyze the roles of architectural proteins and functional elements in blocking long-range contacts between loci. The proposed model does not rely on topologically associating domain (TAD) mapping from Hi-C data. Instead of testing the enrichment or influence of protein binding at TAD borders, the model directly estimates the blocking effect of proteins on long-range contacts between flanking loci, making the model intuitive and biologically meaningful.
Author: Raphael Mourad
Maintainer: Raphael Mourad <raphael.mourad@ibcg.biotoul.fr>

Diff between HiCblock versions 1.4 dated 2018-04-18 and 1.5 dated 2019-08-20

 DESCRIPTION             |    8 ++++----
 MD5                     |   10 +++++-----
 R/HiCblockMiscFun.R     |    2 +-
 build/partial.rdb       |binary
 data/dataExample.RData  |binary
 man/HiCblock-package.Rd |    4 ++++
 6 files changed, 14 insertions(+), 10 deletions(-)

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New package disk.frame with initial version 0.1.0
Type: Package
Package: disk.frame
Title: Larger-than-RAM Disk-Based Data Manipulation Framework
Version: 0.1.0
Date: 2019-08-03
Authors@R: person("Dai", "ZJ", email = "zhuojia.dai@gmail.com", role = c("aut", "cre"))
Maintainer: Dai ZJ <zhuojia.dai@gmail.com>
Description: A disk-based data manipulation tool for working with arbitrarily large datasets as long as they fit on disk.
License: MIT + file LICENSE
Imports: Rcpp (>= 0.12.13), glue (>= 1.3.1), rlang (>= 0.4.0), furrr (>= 0.1.0), future.apply (>= 1.3.0), fs (>= 1.3.1), jsonlite (>= 1.6), pryr (>= 0.1.4), stringr (>= 1.4.0), fst (>= 0.8.0), assertthat (>= 0.2.1), globals (>= 0.12.4), future (>= 1.14.0), data.table (>= 1.12.2), crayon (>= 1.3.4)
Depends: R (>= 3.5.0), dplyr (>= 0.8.3), purrr (>= 0.3.2)
Suggests: testthat, knitr, rmarkdown, nycflights13, magrittr, shiny
LinkingTo: Rcpp
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
URL: http://diskframe.com
BugReports: https://github.com/xiaodaigh/disk.frame/issues
NeedsCompilation: yes
Packaged: 2019-08-19 13:19:13 UTC; RTX2080
Author: Dai ZJ [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-20 10:10:02 UTC

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Package dexterMST updated to version 0.1.2 with previous version 0.1.1 dated 2018-10-29

Title: CML Calibration of Multi Stage Tests
Description: Conditional Maximum Likelihood Calibration and data management of multistage tests. Functions for calibration of the Extended Nominal Response and the Interaction models, DIF and profile analysis. See Robert J. Zwitser and Gunter Maris (2015)<doi:10.1007/s11336-013-9369-6>.
Author: Timo Bechger [aut, cre], Jesse Koops [aut], Ivailo Partchev [aut], Gunter Maris [aut], Robert Zwitser [ctb]
Maintainer: Timo Bechger <tmbechger@gmail.com>

Diff between dexterMST versions 0.1.1 dated 2018-10-29 and 0.1.2 dated 2019-08-20

 dexterMST-0.1.1/dexterMST/tests/Rversions.R                     |only
 dexterMST-0.1.2/dexterMST/DESCRIPTION                           |   10 
 dexterMST-0.1.2/dexterMST/MD5                                   |   29 
 dexterMST-0.1.2/dexterMST/NEWS                                  |    8 
 dexterMST-0.1.2/dexterMST/R/anon.R                              |    2 
 dexterMST-0.1.2/dexterMST/R/data_selection.R                    |    8 
 dexterMST-0.1.2/dexterMST/R/misc.R                              |    4 
 dexterMST-0.1.2/dexterMST/R/mst.R                               |    5 
 dexterMST-0.1.2/dexterMST/R/profile_analysis.R                  |    4 
 dexterMST-0.1.2/dexterMST/inst/doc/multistage_fundamentals.R    |   15 
 dexterMST-0.1.2/dexterMST/inst/doc/multistage_fundamentals.Rmd  |   15 
 dexterMST-0.1.2/dexterMST/inst/doc/multistage_fundamentals.html |  558 ++++++----
 dexterMST-0.1.2/dexterMST/man/reexports.Rd                      |    2 
 dexterMST-0.1.2/dexterMST/src/misc.cpp                          |    2 
 dexterMST-0.1.2/dexterMST/tests/testthat/test_inputs.R          |    9 
 dexterMST-0.1.2/dexterMST/vignettes/multistage_fundamentals.Rmd |   15 
 16 files changed, 451 insertions(+), 235 deletions(-)

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New package testequavar with initial version 0.1.2
Package: testequavar
Type: Package
Title: Bootstrap Tests for Equality of 2, 3, or 4 Population Variances
Version: 0.1.2
Author: Dexter Cahoy
Maintainer: Dexter Cahoy <cahoyd@uhd.edu>
Description: Tests the hypothesis that variances are homogeneous or not using bootstrap. The procedure uses a variance-based statistic, and is derived from a normal-theory test. The test equivalently expressed the hypothesis as a function of the log contrasts of the population variances. A box-type acceptance region is constructed to test the hypothesis. See Cahoy (2010) <doi:10.1016/j.csda.2010.04.012>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: stats
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 12:27:57 UTC; cahoyd
Repository: CRAN
Date/Publication: 2019-08-20 09:30:02 UTC

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New package TestDesign with initial version 0.2.2
Package: TestDesign
Type: Package
Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Version: 0.2.2
Date: 2019-08-10
Authors@R: c( person("Seung W.", "Choi", email = "schoi@austin.utexas.edu", role = c("aut", "cre")), person("Sangdon", "Lim", email = "sangdonlim@utexas.edu", role = "aut"))
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>
Description: Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads>. See vignette for installing 'Rsymphony' package on Mac systems.
License: GPL (>= 2)
Depends: R (>= 2.10)
Imports: Rcpp (>= 1.0.0), methods, Matrix, lpSolve, foreach, logitnorm, Rdpack, crayon
Suggests: gurobi, Rsymphony, Rglpk, shiny, shinythemes, shinyWidgets, shinyjs, DT, knitr, rmarkdown, testthat (>= 2.1.0)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
RdMacros: Rdpack
VignetteBuilder: knitr
Collate: 'import.R' 'RcppExports.R' 'item_class.R' 'item_functions.R' 'loading_functions.R' 'ATA_class.R' 'ATA_functions.R' 'solver_functions.R' 'shadow_class.R' 'shadow_functions.R' 'datasets.R' 'runshiny.R'
NeedsCompilation: yes
Packaged: 2019-08-19 00:17:52 UTC; chois1
Author: Seung W. Choi [aut, cre], Sangdon Lim [aut]
Repository: CRAN
Date/Publication: 2019-08-20 09:10:05 UTC

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New package ssr with initial version 0.1.0
Package: ssr
Type: Package
Title: Semi-Supervised Regression Methods
Version: 0.1.0
Authors@R: c(person("Enrique", "Garcia-Ceja", role = c("aut", "cre"), email = "e.g.mx@ieee.org", comment = c(ORCID = "0000-0001-6864-8557")))
Description: An implementation of semi-supervised regression methods including self-learning and co-training by committee based on Hady, M. F. A., Schwenker, F., & Palm, G. (2009) <doi:10.1007/978-3-642-04274-4_13>. Users can define which set of regressors to use as base models from the 'caret' package, other packages, or custom functions.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/enriquegit/ssr
BugReports: https://github.com/enriquegit/ssr/issues
LazyData: true
Imports: caret
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tgp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-19 12:20:47 UTC; enriqueg
Author: Enrique Garcia-Ceja [aut, cre] (<https://orcid.org/0000-0001-6864-8557>)
Maintainer: Enrique Garcia-Ceja <e.g.mx@ieee.org>
Repository: CRAN
Date/Publication: 2019-08-20 09:30:05 UTC

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New package rSPDE with initial version 0.4.6
Package: rSPDE
Type: Package
Date: 2019-08-19
Title: Rational Approximations of Fractional Stochastic Partial Differential Equations
Version: 0.4.6
Authors@R: person("David","Bolin", email = "davidbolin@gmail.com", role = c("cre", "aut"))
Maintainer: David Bolin <davidbolin@gmail.com>
Description: Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main reference for the methods is Bolin and Kirchner (2019) <arXiv:1711.04333>, which can be generated by the citation function in R.
Depends: R (>= 3.2.0), Matrix
Imports: stats
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, INLA (>= 0.0-1468840039), testthat, excursions
Additional_repositories: https://inla.r-inla-download.org/R/stable
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-19 10:55:52 UTC; davidbolin
Author: David Bolin [cre, aut]
Repository: CRAN
Date/Publication: 2019-08-20 09:10:02 UTC

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New package noisyCE2 with initial version 1.0.0
Package: noisyCE2
Type: Package
Title: Cross-Entropy Optimisation of Noisy Functions
Date: 2019-08-15
Version: 1.0.0
Authors@R: person(given = "Flavio", family = "Santi", role = c("cre", "aut"), email = "flavio.santi@univr.it", comment = c(ORCID = "0000-0002-2014-1981"))
Author: Flavio Santi [cre, aut] (<https://orcid.org/0000-0002-2014-1981>)
Maintainer: Flavio Santi <flavio.santi@univr.it>
URL: https://www.flaviosanti.it/software/noisyCE2
BugReports: https://github.com/f-santi/noisyCE2
Description: Cross-Entropy optimisation of unconstrained deterministic and noisy functions illustrated in Rubinstein and Kroese (2004, ISBN: 978-1-4419-1940-3) through a highly flexible and customisable function which allows user to define custom variable domains, sampling distributions, updating and smoothing rules, and stopping criteria. Several built-in methods and settings make the package very easy-to-use under standard optimisation problems.
Imports: magrittr
Suggests: coda
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 12:51:27 UTC; flavio
Repository: CRAN
Date/Publication: 2019-08-20 09:50:02 UTC

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Package monotonicity updated to version 1.3 with previous version 1.2 dated 2019-02-14

Title: Test for Monotonicity in Expected Asset Returns, Sorted by Portfolios
Description: Test for monotonicity in financial variables sorted by portfolios. It is conventional practice in empirical research to form portfolios of assets ranked by a certain sort variable. A t-test is then used to consider the mean return spread between the portfolios with the highest and lowest values of the sort variable. Yet comparing only the average returns on the top and bottom portfolios does not provide a sufficient way to test for a monotonic relation between expected returns and the sort variable. This package provides nonparametric tests for the full set of monotonic patterns by Patton, A. and Timmermann, A. (2010) <doi:10.1016/j.jfineco.2010.06.006> and compares the proposed results with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.
Author: Siegfried Köstlmeier [aut, cre, trl] (<https://orcid.org/0000-0002-7221-6981>)
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

Diff between monotonicity versions 1.2 dated 2019-02-14 and 1.3 dated 2019-08-20

 DESCRIPTION                             |   10 
 LICENSE                                 |   14 -
 MD5                                     |   60 ++---
 NAMESPACE                               |   34 +--
 R/SB_variance.R                         |   84 +++----
 R/matrix_conversion.R                   |   64 ++---
 R/monoBonferroni.R                      |  102 ++++-----
 R/monoRelation.R                        |  342 ++++++++++++++++----------------
 R/monoSummary.R                         |  194 +++++++++---------
 R/monoUpDown.R                          |  226 ++++++++++-----------
 R/newey_west.R                          |   56 ++---
 R/specify_decimal.R                     |    6 
 R/statBootstrap.R                       |  106 ++++-----
 R/wolak.R                               |  266 ++++++++++++------------
 THANKS                                  |    7 
 build/partial.rdb                       |binary
 man/demo_returns.Rd                     |   56 ++---
 man/monoBonferroni.Rd                   |  116 +++++-----
 man/monoRelation.Rd                     |  112 +++++-----
 man/monoSummary.Rd                      |  143 +++++++------
 man/monoUpDown.Rd                       |   92 ++++----
 man/statBootstrap.Rd                    |   74 +++---
 man/wolak.Rd                            |  147 +++++++------
 tests/testthat.R                        |   24 +-
 tests/testthat/test-matrix_conversion.R |only
 tests/testthat/test-monoBonferroni.R    |   23 +-
 tests/testthat/test-monoRelation.R      |   65 +++---
 tests/testthat/test-monoSummary.R       |   74 ++++--
 tests/testthat/test-monoUpDown.R        |   59 +++--
 tests/testthat/test-specify_decimal.R   |   36 +--
 tests/testthat/test-statBootstrap.R     |only
 tests/testthat/test-wolak.R             |   46 ++--
 32 files changed, 1360 insertions(+), 1278 deletions(-)

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Package ggforce updated to version 0.3.1 with previous version 0.3.0 dated 2019-08-09

Title: Accelerating 'ggplot2'
Description: The aim of 'ggplot2' is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialised plots. 'ggforce' aims to be a collection of mainly new stats and geoms that fills this gap. All additional functionality is aimed to come through the official extension system so using 'ggforce' should be a stable experience.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between ggforce versions 0.3.0 dated 2019-08-09 and 0.3.1 dated 2019-08-20

 DESCRIPTION        |    6 ++---
 MD5                |   36 ++++++++++++++++-----------------
 NEWS.md            |    4 +++
 R/arc_bar.R        |    5 ++--
 R/bezier.R         |   57 ++++++++++++++++++++++++++++++++++++++++++++++++-----
 R/bspline.R        |    3 ++
 R/bspline_closed.R |    3 ++
 R/diagonal.R       |   16 +++++++-------
 R/diagonal_wide.R  |    4 +--
 R/ellipse.R        |    8 +++----
 R/link.R           |   25 ++++++++++++++++++++++-
 R/mark_circle.R    |    4 ++-
 R/mark_ellipse.R   |    4 ++-
 R/mark_hull.R      |    4 ++-
 R/mark_rect.R      |    4 ++-
 R/regon.R          |    2 -
 R/spiro.R          |   14 ++++++-------
 R/voronoi.R        |    4 +--
 README.md          |    9 +++-----
 19 files changed, 150 insertions(+), 62 deletions(-)

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Package crseEventStudy updated to version 1.2 with previous version 1.1 dated 2019-02-13

Title: A Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies
Description: Based on Dutta et al. (2018) <doi:10.1016/j.jempfin.2018.02.004>, this package provides their standardized test for abnormal returns in long-horizon event studies. The methods used improve the major weaknesses of size, power, and robustness of long-run statistical tests described in Kothari/Warner (2007) <doi:10.1016/B978-0-444-53265-7.50015-9>. Abnormal returns are weighted by their statistical precision (i.e., standard deviation), resulting in abnormal standardized returns. This procedure efficiently captures the heteroskedasticity problem. Clustering techniques following Cameron et al. (2011) <10.1198/jbes.2010.07136> are adopted for computing cross-sectional correlation robust standard errors. The statistical tests in this package therefore accounts for potential biases arising from returns' cross-sectional correlation, autocorrelation, and volatility clustering without power loss.
Author: Siegfried Köstlmeier [aut, cre] (<https://orcid.org/0000-0002-7221-6981>), Seppo Pynnonen [aut]
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

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Package birdring updated to version 1.4 with previous version 1.3 dated 2015-10-13

Title: Methods to Analyse Ring Re-Encounter Data
Description: R functions to read EURING data and analyse re-encounter data of birds marked by metal rings. For a tutorial, go to <http://www.tandfonline.com/doi/full/10.1080/03078698.2014.933053>.
Author: Fraenzi Korner-Nievergelt, Rob Robinson
Maintainer: Fraenzi Korner-Nievergelt <fraenzi.korner@vogelwarte.ch>

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Package readabs updated to version 0.4.1 with previous version 0.4.0 dated 2019-06-07

Title: Download and Tidy Time Series Data from the Australian Bureau of Statistics
Description: Downloads, imports, and tidies time series data from the Australian Bureau of Statistics <https://www.abs.gov.au/>.
Author: Matt Cowgill [aut, cre], Zoe Meers [aut], Jaron Lee [aut], David Diviny [ctb]
Maintainer: Matt Cowgill <mattcowgill@gmail.com>

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Package pksensi updated to version 1.1.3 with previous version 1.1.2 dated 2019-06-30

Title: Global Sensitivity Analysis in Physiologically Based Kinetic Modeling
Description: Applying the global sensitivity analysis workflow to investigate the parameter uncertainty and sensitivity in pharmacokinetic (PK) models, especially the physiologically-based pharmacokinetic (PBPK) model with multivariate outputs. The package also provide some functions to check the sensitivity measures and its convergence of model parameters.
Author: Nan-Hung Hsieh [aut, cre] (<https://orcid.org/0000-0003-0163-2766>), Brad Reisfeld [aut], Weihsueh A. Chiu [aut] (<https://orcid.org/0000-0002-7575-2368>)
Maintainer: Nan-Hung Hsieh <nhsieh@cvm.tamu.edu>

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Package photobiologyInOut updated to version 0.4.21 with previous version 0.4.20 dated 2019-06-15

Title: Read Spectral and Logged Data from Foreign Files
Description: Functions for reading, and in some cases writing, foreign files containing spectral data from spectrometers and their associated software, output from daylight simulation models in common use, and some spectral data repositories. As well as functions for exchange of spectral data with other R packages. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (<https://orcid.org/0000-0002-2822-9734>), Glenn Davis [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package paws.common updated to version 0.2.0 with previous version 0.1.2 dated 2019-08-08

Title: Paws Low-Level Amazon Web Services API
Description: Functions for making low-level API requests to Amazon Web Services <https://aws.amazon.com>. The functions handle building, signing, and sending requests, and receiving responses. They are designed to help build higher-level interfaces to individual services, such as Simple Storage Service (S3).
Author: David Kretch [aut, cre], Adam Banker [aut], Amazon.com, Inc. [cph]
Maintainer: David Kretch <david.kretch@gmail.com>

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Package icarus updated to version 0.3.1 with previous version 0.3.0 dated 2017-03-04

Title: Calibrates and Reweights Units in Samples
Description: Provides user-friendly tools for calibration in survey sampling. The package is production-oriented, and its interface is inspired by the famous popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to 'icarus'. In addition to calibration (with linear, raking and logit methods), 'icarus' features functions for calibration on tight bounds and penalized calibration.
Author: Antoine Rebecq [aut, cre]
Maintainer: Antoine Rebecq <antoine.rebecq@m4x.org>

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Package dst updated to version 1.4.0 with previous version 1.3.0 dated 2018-12-05

Title: Using the Theory of Belief Functions
Description: Using the Theory of Belief Functions for evidence calculus. Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values and combined. A mass function can be extended to a larger frame. Marginalization, i.e. reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks and take into account situations where information cannot be satisfactorily described by probability distributions.
Author: Claude Boivin, Stat.ASSQ <webapp.cb@gmail.com>
Maintainer: Claude Boivin <webapp.cb@gmail.com>

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