Sat, 17 Nov 2018

Package valr updated to version 0.4.2 with previous version 0.4.1 dated 2018-06-08

Title: Genome Interval Arithmetic in R
Description: Read and manipulate genome intervals and signals. Provides functionality similar to command-line tool suites within R, enabling interactive analysis and visualization of genome-scale data.
Author: Jay Hesselberth [aut, cre] (<https://orcid.org/0000-0002-6299-179X>), Kent Riemondy [aut] (<https://orcid.org/0000-0003-0750-1273>)
Maintainer: Jay Hesselberth <jay.hesselberth@gmail.com>

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Package rcites updated to version 1.0.0 with previous version 0.1.0 dated 2018-08-11

Title: R Interface to the Species+ Database
Description: A programmatic interface to the Species+ <https://speciesplus.net/> database via the Species+/CITES Checklist API <https://api.speciesplus.net/>.
Author: Jonas Geschke [aut] (<https://orcid.org/0000-0002-5654-9313>), Kevin Cazelles [aut, cre] (<https://orcid.org/0000-0001-6619-9874>), Ignasi Bartomeus [aut] (<https://orcid.org/0000-0001-7893-4389>), Jonathan Goldenberg [ctb], Marie-Bé Leduc [ctb], Yasmine Verzelen [ctb], Noam Ross [rev], Margaret Siple [rev]
Maintainer: Kevin Cazelles <kevin.cazelles@gmail.com>

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New package PDFEstimator with initial version 0.1-1
Package: PDFEstimator
Version: 0.1-1
Date: 2018-11-7
Title: Nonparametric Probability Density Estimator
Author: Jenny Farmer <jfarmer6@uncc.edu> and Donald Jacobs <djacobs1@uncc.ecu>
Maintainer: Jenny Farmer <jfarmer6@uncc.edu>
Description: A nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2018-11-16 23:47:56 UTC; jenny
Repository: CRAN
Date/Publication: 2018-11-18 00:50:19 UTC

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New package fungible with initial version 1.75
Package: fungible
Version: 1.75
Date: 2018-11-16
Title: Psychometric Functions from the Waller Lab
Author: c( person("Niels", "Waller", role = c("aut", "cre"), email="nwaller@umn.edu" ), person("Jeff","Jones", role = "ctb"))
Maintainer: Niels G. Waller <nwaller@umn.edu>
Depends: R (>= 3.0)
Imports: clue, e1071, GPArotation, lattice, MASS, methods, mvtnorm, nleqslv, psych, Rcsdp, RSpectra, stringr
Description: Computes fungible coefficients and Monte Carlo data. Underlying theory for these functions is described in the following publications: Waller, N. (2008). Fungible Weights in Multiple Regression. Psychometrika, 73(4), 691-703, <DOI10.1007/s11336-008-9066-z>. Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights. Psychometrika, 74(4), 589-602, <DOI10.1007/s11336-008-9087-7>. Waller, N. G. (2016). Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research. Multivariate Behavioral Research, 51(4), 554-568, <DOI10.1080/00273171.2016.1178566>. Jones, J. A. & Waller, N. G. (2015). The normal-theory and asymptotic distribution-free (ADF) covariance matrix of standardized regression coefficients: theoretical extensions and finite sample behavior. Psychometrika, 80, 365-378, <DOI10.1007/s11336-013-9380-y>. Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. <DOI 10.1007/s11336-017-9599-0>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-11-16 20:34:46 UTC; nielswaller
Repository: CRAN
Date/Publication: 2018-11-18 00:50:14 UTC

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New package Fgmutils with initial version 0.9.5
Package: Fgmutils
Type: Package
Title: Forest Growth Model Utilities
Version: 0.9.5
Date: 2018-10-11
Author: Clayton Vieira Fraga Filho, Ana Paula Simiqueli, Gilson Fernandes da Silva, Miqueias Fernandes, Wagner Amorim da Silva Altoe
Maintainer: Clayton Vieira Fraga Filho <forestgrowthsoftware@gmail.com>
Description: Growth models and forest production require existing data manipulation and the creation of new data, structured from basic forest inventory data. The purpose of this package is provide functions to support these activities.
License: GPL-2
Depends: sqldf, stringr, plyr, R (>= 3.0)
Imports: data.table, tcltk, utils, stats, graphics, devEMF, png, grDevices, methods, ggplot2, gridExtra
LazyData: TRUE
Suggests: testthat
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-17 22:29:47 UTC; clayt
Repository: CRAN
Date/Publication: 2018-11-18 00:50:22 UTC

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Package RiemBase updated to version 0.2.0 with previous version 0.1.0 dated 2018-11-04

Title: Functions and C++ Header Files for Computation on Manifolds
Description: We provide a number of algorithms to estimate fundamental statistics including Fréchet mean and geometric median for manifold-valued data. Also, C++ header files are contained that implement elementary operations on manifolds such as Sphere, Grassmann, and others. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> if you are interested in statistics on manifolds, and Absil et al (2007) <isbn:978-0-691-13298-3> on computational aspects of optimization on matrix manifolds.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

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Package rpdo updated to version 0.2.5 with previous version 0.2.4 dated 2018-08-15

Title: Pacific Decadal Oscillation Index Data
Description: Monthly Pacific Decadal Oscillation (PDO) index values from January 1900 to present.
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Nathan Mantua [aut, dtc], Steven R. Hare [aut, dtc]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

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Package ncpen updated to version 1.0.0 with previous version 0.2.0 dated 2018-02-21

Title: Unified Algorithm for Non-convex Penalized Estimation for Generalized Linear Models
Description: An efficient unified nonconvex penalized estimation algorithm for Gaussian (linear), binomial Logit (logistic), Poisson, multinomial Logit, and Cox proportional hazard regression models. The unified algorithm is implemented based on the convex concave procedure and the algorithm can be applied to most of the existing nonconvex penalties. The algorithm also supports convex penalty: least absolute shrinkage and selection operator (LASSO). Supported nonconvex penalties include smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), truncated LASSO penalty (TLP), clipped LASSO (CLASSO), sparse ridge (SRIDGE), modified bridge (MBRIDGE) and modified log (MLOG). For high-dimensional data (data set with many variables), the algorithm selects relevant variables producing a parsimonious regression model. Kim, D., Lee, S. and Kwon, S. (2018) <arXiv:1811.05061>, Lee, S., Kwon, S. and Kim, Y. (2016) <doi:10.1016/j.csda.2015.08.019>, Kwon, S., Lee, S. and Kim, Y. (2015) <doi:10.1016/j.csda.2015.07.001>. (This research is funded by Julian Virtue Professorship from Center for Applied Research at Pepperdine Graziadio Business School and the National Research Foundation of Korea.)
Author: Dongshin Kim [aut, cre, cph], Sunghoon Kwon [aut, cph], Sangin Lee [aut, cph]
Maintainer: Dongshin Kim <dongshin.kim@live.com>

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Package yearn (with last version 0.1.3) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2018-01-12 0.1.3
2017-06-16 0.1.1

Permanent link
Package svars updated to version 1.2.2 with previous version 1.2.1 dated 2018-08-08

Title: Data-Driven Identification of SVAR Models
Description: Implements data-driven identification methods for structural vector autoregressive (SVAR) models. Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>).
Author: Alexander Lange [aut, cre], Bernhard Dalheimer [aut], Helmut Herwartz [aut], Simone Maxand [aut], Hannes Riebl [ctb]
Maintainer: Alexander Lange <alexander.lange@uni-goettingen.de>

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Package wTO updated to version 1.6.3 with previous version 1.6.2 dated 2018-10-14

Title: Computing Weighted Topological Overlaps (wTO) & Consensus wTO Network
Description: Computes the Weighted Topological Overlap with positive and negative signs (wTO) networks given a data frame containing the mRNA count/ expression/ abundance per sample, and a vector containing the interested nodes of interaction (a subset of the elements of the full data frame). It also computes the cut-off threshold or p-value based on the individuals bootstrap or the values reshuffle per individual. It also allows the construction of a consensus network, based on multiple wTO networks. The package includes a visualization tool for the networks. More about the methodology can be found at <arXiv:1711.04702>.
Author: Deisy Morselli Gysi, Andre Voigt, Tiago Miranda Fragoso, Eivind Almaas and Katja Nowick.
Maintainer: Deisy Morselli Gysi <deisy@bioinf.uni-leipzig.de>

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Package mclust updated to version 5.4.2 with previous version 5.4.1 dated 2018-06-27

Title: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Description: Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
Author: Chris Fraley [aut], Adrian E. Raftery [aut], Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>), Michael Fop [ctb] (<https://orcid.org/0000-0003-3936-2757>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package ggeffects updated to version 0.7.0 with previous version 0.6.0 dated 2018-10-11

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The two main functions are ggpredict() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package jmvconnect updated to version 1.0.5 with previous version 1.0.4 dated 2018-08-11

Title: Connect to the 'jamovi' Statistical Spreadsheet
Description: Methods to access data sets from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information) from R.
Author: Jonathon Love [aut, cre]
Maintainer: Jonathon Love <jon@thon.cc>

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Package dslice updated to version 1.2.0 with previous version 1.1.5 dated 2015-11-16

Title: Dynamic Slicing
Description: Dynamic slicing is a method designed for dependency detection between a categorical variable and a continuous variable. It could be applied for non-parametric hypothesis testing and gene set enrichment analysis.
Author: Chao Ye and Bo Jiang
Maintainer: Chao Ye <yechao1009@gmail.com>

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