Wed, 13 Apr 2022

Package mlogitBMA updated to version 0.1-7 with previous version 0.1-6 dated 2013-12-11

Title: Bayesian Model Averaging for Multinomial Logit Models
Description: Provides a modified function bic.glm of the BMA package that can be applied to multinomial logit (MNL) data. The data is converted to binary logit using the Begg & Gray approximation. The package also contains functions for maximum likelihood estimation of MNL.
Author: Hana Sevcikova, Adrian Raftery
Maintainer: Hana Sevcikova <hanas@uw.edu>

Diff between mlogitBMA versions 0.1-6 dated 2013-12-11 and 0.1-7 dated 2022-04-13

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Package MGLM updated to version 0.2.1 with previous version 0.2.0 dated 2018-10-19

Title: Multivariate Response Generalized Linear Models
Description: Provides functions that (1) fit multivariate discrete distributions, (2) generate random numbers from multivariate discrete distributions, and (3) run regression and penalized regression on the multivariate categorical response data. Implemented models include: multinomial logit model, Dirichlet multinomial model, generalized Dirichlet multinomial model, and negative multinomial model. Making the best of the minorization-maximization (MM) algorithm and Newton-Raphson method, we derive and implement stable and efficient algorithms to find the maximum likelihood estimates. On a multi-core machine, multi-threading is supported.
Author: Yiwen Zhang <zhangyiwen1015@gmail.com> and Hua Zhou <huazhou@ucla.edu>
Maintainer: Juhyun Kim <juhkim111@ucla.edu>

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Package scales updated to version 1.2.0 with previous version 1.1.1 dated 2020-05-11

Title: Scale Functions for Visualization
Description: Graphical scales map data to aesthetics, and provide methods for automatically determining breaks and labels for axes and legends.
Author: Hadley Wickham [aut, cre], Dana Seidel [aut], RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package Dasst updated to version 0.3.4 with previous version 0.3.3 dated 2017-11-13

Title: Tools for Reading, Processing and Writing 'DSSAT' Files
Description: Provides methods for reading, displaying, processing and writing files originally arranged for the 'DSSAT-CSM' fixed width format. The 'DSSAT-CSM' cropping system model is described at J.W. Jones, G. Hoogenboomb, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, J.T. Ritchie (2003) <doi:10.1016/S1161-0301(02)00107-7>.
Author: Homero Lozza [aut, cre]
Maintainer: Homero Lozza <homerolozza@gmail.com>

Diff between Dasst versions 0.3.3 dated 2017-11-13 and 0.3.4 dated 2022-04-13

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Package tiledb updated to version 0.12.0 with previous version 0.11.1 dated 2022-03-25

Title: Universal Storage Engine for Sparse and Dense Multidimensional Arrays
Description: The universal storage engine 'TileDB' introduces a powerful on-disk format for multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations.
Author: TileDB, Inc. [aut, cph], Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>

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Package mem updated to version 2.17 with previous version 2.16 dated 2020-09-13

Title: The Moving Epidemic Method
Description: The Moving Epidemic Method, created by T Vega and JE Lozano (2012, 2015) <doi:10.1111/j.1750-2659.2012.00422.x>, <doi:10.1111/irv.12330>, allows the weekly assessment of the epidemic and intensity status to help in routine respiratory infections surveillance in health systems. Allows the comparison of different epidemic indicators, timing and shape with past epidemics and across different regions or countries with different surveillance systems. Also, it gives a measure of the performance of the method in terms of sensitivity and specificity of the alert week.
Author: Jose E. Lozano [aut, cre]
Maintainer: Jose E. Lozano <lozalojo@gmail.com>

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Package lars updated to version 1.3 with previous version 1.2 dated 2013-04-24

Title: Least Angle Regression, Lasso and Forward Stagewise
Description: Efficient procedures for fitting an entire lasso sequence with the cost of a single least squares fit. Least angle regression and infinitesimal forward stagewise regression are related to the lasso, as described in the paper below.
Author: Trevor Hastie <hastie@stanford.edu> and Brad Efron <brad@stat.stanford.edu>
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package dynatopGIS updated to version 0.2.2 with previous version 0.2.1 dated 2022-01-07

Title: Algorithms for Helping Build Dynamic TOPMODEL Implementations from Spatial Data
Description: A set of algorithms based on Quinn et al. (1991) <doi:10.1002/hyp.3360050106> for processing river network and digital elevation data to build implementations of Dynamic TOPMODEL, a semi-distributed hydrological model proposed in Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements simulation code for Dynamic TOPMODEL based on the output of 'dynatopGIS'.
Author: Paul Smith [aut, cre]
Maintainer: Paul Smith <paul@waternumbers.co.uk>

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Package dynatop updated to version 0.2.2 with previous version 0.2.1 dated 2022-01-18

Title: An Implementation of Dynamic TOPMODEL Hydrological Model in R
Description: An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed hydrological model originally proposed by Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements code for simulating models which can be created using the 'dynatopGIS' package.
Author: Paul Smith [aut, cre] , Peter Metcalfe [aut]
Maintainer: Paul Smith <paul@waternumbers.co.uk>

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Package caribou updated to version 1.1-1 with previous version 1.1 dated 2012-06-11

Title: Estimation of Caribou Abundance Based on Radio Telemetry Data
Description: Estimation of population size of migratory caribou herds based on large scale aggregations monitored by radio telemetry. It implements the methodology found in the article by Rivest et al. (1998) about caribou abundance estimation. It also includes a function based on the Lincoln-Petersen Index as applied to radio telemetry data by White and Garrott (1990).
Author: Louis-Paul Rivest [aut, cre], Helene Crepeau [aut], Serge Couturier [ctb], Sophie Baillargeon [aut]
Maintainer: Louis-Paul Rivest <Louis-Paul.Rivest@mat.ulaval.ca>

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Package themis updated to version 0.2.1 with previous version 0.2.0 dated 2022-03-30

Title: Extra Recipes Steps for Dealing with Unbalanced Data
Description: A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arXiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
Author: Emil Hvitfeldt [aut, cre]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package cutpointr updated to version 1.1.2 with previous version 1.1.1 dated 2021-06-29

Title: Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks
Description: Estimate cutpoints that optimize a specified metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included. For an overview of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.
Author: Christian Thiele [cre, aut]
Maintainer: Christian Thiele <c.thiele@gmx-topmail.de>

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Package hutils updated to version 1.8.1 with previous version 1.7.1 dated 2021-07-22

Title: Miscellaneous R Functions and Aliases
Description: Provides utility functions for, and drawing on, the 'data.table' package. The package also collates useful miscellaneous functions extending base R not available elsewhere. The name is a portmanteau of 'utils' and the author.
Author: Hugh Parsonage [aut, cre], Michael Frasco [ctb], Ben Hamner [ctb]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

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Package EcoTroph updated to version 1.6.1 with previous version 1.6 dated 2013-09-13

Title: An Implementation of the EcoTroph Ecosystem Modelling Approach
Description: An approach and software for modelling marine and freshwater ecosystems. It is articulated entirely around trophic levels. EcoTroph's key displays are bivariate plots, with trophic levels as the abscissa, and biomass flows or related quantities as ordinates. Thus, trophic ecosystem functioning can be modelled as a continuous flow of biomass surging up the food web, from lower to higher trophic levels, due to predation and ontogenic processes. Such an approach, wherein species as such disappear, may be viewed as the ultimate stage in the use of the trophic level metric for ecosystem modelling, providing a simplified but potentially useful caricature of ecosystem functioning and impacts of fishing. This version contains catch trophic spectrum analysis (CTSA) function and corrected versions of the mf.diagnosis and create.ETmain functions.
Author: J. Guitton, M. Colleter, P. Gatti, and D. Gascuel
Maintainer: Jerome Guitton <jerome.guitton@agrocampus-ouest.fr>

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Package dowser updated to version 1.0.0 with previous version 0.1.0 dated 2021-07-22

Title: B Cell Receptor Phylogenetics Toolkit
Description: Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. Provides methods to 1) reconstruct unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple methods, 3) visualize trees with metadata at the tips, 4) reconstruct intermediate sequences, 5) detect biased ancestor-descendant relationships among metadata types Workflow examples available at documentation site (see URL). Citations: Hoehn et al (2020) <doi:10.1101/2020.05.30.124446>, Hoehn et al (2021) <doi:10.1101/2021.01.06.425648>.
Author: Kenneth Hoehn [aut, cre], Susanna Marquez [ctb], Jason Vander Heiden [ctb], Steven Kleinstein [aut, cph]
Maintainer: Kenneth Hoehn <kenneth.hoehn@yale.edu>

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Package bruceR updated to version 0.8.6 with previous version 0.8.5 dated 2022-03-02

Title: Broadly Useful Convenient and Efficient R Functions
Description: Broadly useful convenient and efficient R functions that bring users concise and elegant R data analyses. This package includes easy-to-use functions for (1) basic R programming (e.g., set working directory to the path of currently opened file, import/export data from/to files with any format, print strings with rich formats and colors); (2) multivariate computation (e.g., compute scale sums/means/... with reverse scoring); (3) reliability analyses and factor analyses; (4) descriptive statistics and correlation analyses; (5) t-test, multi-factor analysis of variance (ANOVA), simple-effect analysis, and post-hoc multiple comparison; (6) tidy report of statistical models (to R Console and Microsoft Word); (7) mediation and moderation analyses (PROCESS); and (8) additional toolbox for statistics and graphics.
Author: Han-Wu-Shuang Bao [aut, cre]
Maintainer: Han-Wu-Shuang Bao <baohws@foxmail.com>

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Package broom updated to version 0.8.0 with previous version 0.7.12 dated 2022-01-28

Title: Convert Statistical Objects into Tidy Tibbles
Description: Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Author: David Robinson [aut], Alex Hayes [aut] , Simon Couch [aut, cre] , RStudio [cph, fnd], Indrajeet Patil [ctb] , Derek Chiu [ctb], Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Ben Bolker [ct [...truncated...]
Maintainer: Simon Couch <simonpatrickcouch@gmail.com>

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Package wrMisc updated to version 1.9.1 with previous version 1.9.0 dated 2022-03-25

Title: Analyze Experimental High-Throughput (Omics) Data
Description: The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. Many times large experimental datasets need some additional filtering, adequate functions are provided. Batch reading (or writing) of sets of files and combining data to arrays is supported, too. Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

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Package stratallo updated to version 2.0.1 with previous version 2.0.0 dated 2022-04-12

Title: Optimum Sample Allocation in Stratified Sampling Schemes
Description: Functions in this package provide solution to classical problem in survey methodology - an optimum sample allocation in stratified sampling schemes. In this context, the optimal allocation is in the classical Tschuprov-Neyman's sense and it satisfies additional either lower or upper bounds restrictions imposed on sample sizes in strata. There are few different algorithms available to use, and one them is based on popular sample allocation method that applies Neyman allocation to recursively reduced set of strata. This package also provides the function that computes a solution to the minimum sample size allocation problem, which is a minor modification of the classical optimium sample allocation. This problems lies in the determination of a vector of strata sample sizes that minimizes total sample size, under assumed fixed level of the pi-estimator's variance. As in the case of the classical optimal allocation, the problem of minimum sample size allocation can be complemented by imposing upper bounds constraints on sample sizes in strata.
Author: Wojciech Wojciak [aut, cre], Jacek Wesolowski [sad], Robert Wieczorkowski [ctb]
Maintainer: Wojciech Wojciak <wojciech.wojciak@gmail.com>

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Package mstrio updated to version 11.3.5.101 with previous version 11.3.0.1 dated 2020-12-21

Title: Interface for 'MicroStrategy' REST API
Description: Interface for creating data sets and extracting data through the 'MicroStrategy' REST API. Access the demo API at <https://demo.microstrategy.com/MicroStrategyLibrary/api-docs/index.html>.
Author: Piotr Kowal [aut, cre]
Maintainer: Piotr Kowal <pkowal@microstrategy.com>

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Package glmmML updated to version 1.1.2 with previous version 1.1.1 dated 2020-05-28

Title: Generalized Linear Models with Clustering
Description: Binomial and Poisson regression for clustered data, fixed and random effects with bootstrapping.
Author: Goeran Brostroem [aut, cre], Jianming Jin [ctb], Henrik Holmberg [ctb]
Maintainer: Goeran Brostroem <goran.brostrom@umu.se>

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Package brms updated to version 2.17.0 with previous version 2.16.3 dated 2021-11-22

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Paul-Christian Buerkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb], Hamada S. Badr [ctb], Frank Weber [ctb], Mattan S. Ben-Shachar [ctb], Hayden Rabel [ctb]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>

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Package drat updated to version 0.2.3 with previous version 0.2.2 dated 2021-12-02

Title: 'Drat' R Archive Template
Description: Creation and use of R Repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are support: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.
Author: Dirk Eddelbuettel with contributions by Carl Boettiger, Neal Fultz, Sebastian Gibb, Colin Gillespie, Jan Gorecki, Matt Jones, Thomas Leeper, Steven Pav, Jan Schulz, Christoph Stepper, Felix G.M. Ernst and Patrick Schratz.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package declared updated to version 0.15 with previous version 0.13 dated 2022-04-03

Title: Functions to Declare Missing Values
Description: A set of functions to declare labels and missing values, coupled with associated functions to create (weighted) tables of frequencies and various other summary measures. Various base functions are rewritten to make use of the specific information about the missing values, most importantly to distinguish between empty and declared missing values. Many functions have a similar functionality with the corresponding functions from packages "haven" and "labelled". A lot of effort was spent to ensure as much compatibility as possible with these packages, with the intention to offer a complementary alternative for the objects of class "declared".
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package taxonbridge updated to version 1.2.0 with previous version 1.1.0 dated 2022-04-08

Title: Create Custom Taxonomies Based on the NCBI Taxonomy and GBIF Backbone Taxonomy
Description: The NCBI taxonomy is a popular resource for taxonomic studies but it only contains data on species with sequence data whereas the GBIF has a more extensive coverage of extinct species. Taxonbridge is useful for the creation and analysis of custom taxonomies based on the NCBI taxonomy and GBIF backbone taxonomy.
Author: Werner Veldsman [aut, cre]
Maintainer: Werner Veldsman <wernerpieter.veldsman@unil.ch>

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Package ROpenCVLite updated to version 4.55.0 with previous version 4.52.1 dated 2022-02-17

Title: Helper Package for Installing OpenCV with R
Description: Installs 'OpenCV' for use by other packages. 'OpenCV' <https://opencv.org/> is library of programming functions mainly aimed at real-time computer vision. This 'Lite' version contains the stable base version of 'OpenCV' and does not contain any of its externally contributed modules.
Author: Simon Garnier [aut, cre] , Muschelli John [ctb]
Maintainer: Simon Garnier <garnier@njit.edu>

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Package opendatatoronto updated to version 0.1.5 with previous version 0.1.4 dated 2020-10-14

Title: Access the City of Toronto Open Data Portal
Description: Access data from the "City of Toronto Open Data Portal" (<https://open.toronto.ca>) directly from R.
Author: Sharla Gelfand [aut, cre], City of Toronto [cph, fnd]
Maintainer: Sharla Gelfand <sharla.gelfand@gmail.com>

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Package MCMCpack updated to version 1.6-3 with previous version 1.6-2 dated 2022-03-30

Title: Markov Chain Monte Carlo (MCMC) Package
Description: Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Author: Andrew D. Martin [aut], Kevin M. Quinn [aut], Jong Hee Park [aut,cre], Ghislain Vieilledent [ctb], Michael Malecki[ctb], Matthew Blackwell [ctb], Keith Poole [ctb], Craig Reed [ctb], Ben Goodrich [ctb], Qiushi Yu [ctb], Ross Ihaka [cph], The R Develo [...truncated...]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

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Package Epi updated to version 2.46 with previous version 2.44 dated 2021-02-27

Title: Statistical Analysis in Epidemiology
Description: Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Author: Bendix Carstensen [aut, cre], Martyn Plummer [aut], Esa Laara [ctb], Michael Hills [ctb]
Maintainer: Bendix Carstensen <b@bxc.dk>

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Package embed updated to version 0.2.0 with previous version 0.1.5 dated 2021-11-24

Title: Extra Recipes for Encoding Predictors
Description: Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737> can be used. There are also functions for dimension reduction and other approaches.
Author: Emil Hvitfeldt [aut, cre] , Max Kuhn [aut] , RStudio [cph]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package cartogramR updated to version 1.0-7 with previous version 1.0-6 dated 2022-03-22

Title: Continuous Cartogram
Description: Procedures for making continuous cartogram. Procedures available are: flow based cartogram (Gastner & Newman (2004) <doi:10.1073/pnas.0400280101>), fast flow based cartogram (Gastner, Seguy & More (2018) <doi:10.1073/pnas.1712674115>), rubber band based cartogram (Dougenik et al. (1985) <doi:10.1111/j.0033-0124.1985.00075.x>).
Author: Pierre-Andre Cornillon [aut, cre], Florent Demoraes [aut], Flow-Based-Cartograms [cph]
Maintainer: Pierre-Andre Cornillon <pierre-andre.cornillon@univ-rennes2.fr>

Diff between cartogramR versions 1.0-6 dated 2022-03-22 and 1.0-7 dated 2022-04-13

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Package vctrs updated to version 0.4.1 with previous version 0.4.0 dated 2022-03-30

Title: Vector Helpers
Description: Defines new notions of prototype and size that are used to provide tools for consistent and well-founded type-coercion and size-recycling, and are in turn connected to ideas of type- and size-stability useful for analysing function interfaces.
Author: Hadley Wickham [aut], Lionel Henry [aut, cre], Davis Vaughan [aut], data.table team [cph] and their contribution to R's order), RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between vctrs versions 0.4.0 dated 2022-03-30 and 0.4.1 dated 2022-04-13

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New package UNF with initial version 2.0.8
Package: UNF
Version: 2.0.8
Title: Tools for Creating Universal Numeric Fingerprints for Data
Date: 2022-04-11
Description: Computes a 'universal numeric fingerprint' ('UNF') for an R data object. 'UNF' is a hash or signature that can be used to uniquely identify (a version of) a rectangular dataset, or a subset thereof. 'UNF' can be used, in tandem with a 'DOI', to form a persistent citation to a versioned dataset.
Imports: utils, stats, tools, base64enc, digest
Suggests: knitr, rmarkdown, testthat
License: GPL-2
URL: https://github.com/leeper/UNF
BugReports: https://github.com/leeper/UNF/issues
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-04-12 00:54:21 UTC; THOMAS
Author: Thomas J. Leeper [aut, cre] , Micah Altman [aut]
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>
Repository: CRAN
Date/Publication: 2022-04-13 10:12:36 UTC

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Package neptune updated to version 0.2.3 with previous version 0.2.2 dated 2022-04-06

Title: MLOps Metadata Store - Experiment Tracking and Model Registry for Production Teams
Description: An interface to Neptune. A metadata store for MLOps, built for teams that run a lot of experiments. It gives you a single place to log, store, display, organize, compare, and query all your model-building metadata. Neptune is used for: • Experiment tracking: Log, display, organize, and compare ML experiments in a single place. • Model registry: Version, store, manage, and query trained models, and model building metadata. • Monitoring ML runs live: Record and monitor model training, evaluation, or production runs live For more information see <https://neptune.ai/>.
Author: Mateusz Dominiak [aut], Rafal Jankowski [aut, cre]
Maintainer: Rafal Jankowski <rafal.jankowski@neptune.ai>

Diff between neptune versions 0.2.2 dated 2022-04-06 and 0.2.3 dated 2022-04-13

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Package dlstats updated to version 0.1.5 with previous version 0.1.4 dated 2021-04-23

Title: Download Stats of R Packages
Description: Monthly download stats of 'CRAN' and 'Bioconductor' packages. Download stats of 'CRAN' packages is from the 'RStudio' 'CRAN mirror', see <https://cranlogs.r-pkg.org:443>. 'Bioconductor' package download stats is at <https://bioconductor.org/packages/stats/>.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between dlstats versions 0.1.4 dated 2021-04-23 and 0.1.5 dated 2022-04-13

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New package enveomics.R with initial version 1.9.0
Package: enveomics.R
Version: 1.9.0
Title: Various Utilities for Microbial Genomics and Metagenomics
Description: A collection of functions for microbial ecology and other applications of genomics and metagenomics. Companion package for the Enveomics Collection (Rodriguez-R, L.M. and Konstantinidis, K.T., 2016 <DOI:10.7287/peerj.preprints.1900v1>).
Author: Luis M. Rodriguez-R [aut, cre]
Maintainer: Luis M. Rodriguez-R <lmrodriguezr@gmail.com>
URL: http://enve-omics.ce.gatech.edu/enveomics/
Depends: R (>= 2.9), stats, methods, parallel, fitdistrplus, sn, investr
Suggests: tools, vegan, ape, picante, gplots, optparse
License: Artistic-2.0
LazyData: yes
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-04-12 01:57:47 UTC; miguel
Repository: CRAN
Date/Publication: 2022-04-13 10:12:29 UTC

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Package RNentropy updated to version 1.2.3 with previous version 1.2.2 dated 2018-06-01

Title: Entropy Based Method for the Detection of Significant Variation in Gene Expression Data
Description: An implementation of a method based on information theory devised for the identification of genes showing a significant variation of expression across multiple conditions. Given expression estimates from any number of RNA-Seq samples and conditions it identifies genes or transcripts with a significant variation of expression across all the conditions studied, together with the samples in which they are over- or under-expressed. Zambelli et al. (2018) <doi:10.1093/nar/gky055>.
Author: Federico Zambelli [cre] , Giulio Pavesi [aut]
Maintainer: Federico Zambelli <federico.zambelli@unimi.it>

Diff between RNentropy versions 1.2.2 dated 2018-06-01 and 1.2.3 dated 2022-04-13

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Package ReDaMoR updated to version 0.6.3 with previous version 0.5.2 dated 2022-01-13

Title: Relational Data Modeler
Description: The aim of this package is to manipulate relational data models in R. It provides functions to create, modify and export data models in json format. It also allows importing models created with 'MySQL Workbench' (<https://www.mysql.com/products/workbench/>). These functions are accessible through a graphical user interface made with 'shiny'. Constraints such as types, keys, uniqueness and mandatory fields are automatically checked and corrected when editing a model. Finally, real data can be confronted to a model to check their compatibility.
Author: Patrice Godard [aut, cre, cph]
Maintainer: Patrice Godard <patrice.godard@gmail.com>

Diff between ReDaMoR versions 0.5.2 dated 2022-01-13 and 0.6.3 dated 2022-04-13

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Package matlab2r updated to version 1.1.0 with previous version 1.0.0 dated 2022-01-28

Title: Translation Layer from MATLAB to R
Description: Allows users familiar with MATLAB to use MATLAB-named functions in R. Several basic MATLAB functions are written in this package to mimic the behavior of their original counterparts, with more to come as this package grows.
Author: Waldir Leoncio [aut, cre]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

Diff between matlab2r versions 1.0.0 dated 2022-01-28 and 1.1.0 dated 2022-04-13

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New package LTASR with initial version 0.0.1
Package: LTASR
Title: Functions to Replicate the Center for Disease Control and Prevention's 'LTAS' Software in R
Version: 0.0.1
Description: A suite of functions for reading in a rate file in XML format, stratify a cohort, and calculate 'SMRs' from the stratified cohort and rate file.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, knitr, lubridate, magrittr, purrr, readr, rlang, stringr, tidyr, XML, zoo
Suggests: rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 2.10)
LazyData: true
NeedsCompilation: no
Packaged: 2022-04-11 21:11:59 UTC; inh4
Author: Stephen Bertke [aut, cre]
Maintainer: Stephen Bertke <nioshltas@cdc.gov>
Repository: CRAN
Date/Publication: 2022-04-13 09:02:29 UTC

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New package svines with initial version 0.1.4
Package: svines
Title: Stationary Vine Copula Models
Version: 0.1.4
Description: Provides functionality to fit and simulate from stationary vine copula models for time series, see Nagler et al. (2022) <doi:10.1016/j.jeconom.2021.11.015>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/tnagler/svines
BugReports: https://github.com/tnagler/svines/issues
Depends: R (>= 3.3.0), rvinecopulib (>= 0.6.1.1.2)
Imports: Rcpp, assertthat, univariateML, wdm, fGarch
LinkingTo: RcppEigen, Rcpp, RcppThread, BH, wdm, rvinecopulib
Suggests: testthat, ggraph, covr
NeedsCompilation: yes
Packaged: 2022-04-08 09:02:28 UTC; n5
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <mail@tnagler.com>
Repository: CRAN
Date/Publication: 2022-04-13 08:20:02 UTC

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Package spOccupancy updated to version 0.3.1 with previous version 0.3.0 dated 2022-03-29

Title: Single-Species, Multi-Species, and Integrated Spatial Occupancy Models
Description: Fits single-species, multi-species, and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2020) <arXiv:2001.09111>. Provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. Details on data integration are given in Miller, Pacifici, Sanderlin, and Reich (2019) <doi:10.1111/2041-210X.13110>. Details on single-species and multi-species models are found in MacKenzie, Nichols, Lachman, Droege, Royle, and Langtimm (2002) <doi:10.1890/0012-9658(2002)083[2248:ESORWD]2.0.CO;2> and Dorazio and Royle <doi:10.1198/016214505000000015>, respectively.
Author: Jeffrey Doser [aut, cre], Andrew Finley [aut]
Maintainer: Jeffrey Doser <doserjef@msu.edu>

Diff between spOccupancy versions 0.3.0 dated 2022-03-29 and 0.3.1 dated 2022-04-13

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New package pspatreg with initial version 1.0.0
Package: pspatreg
Title: Spatial and Spatio-Temporal Semiparametric Regression Models with Spatial Lags
Version: 1.0.0
Date: 2022-04-07
Maintainer: Roman Minguez <roman.minguez@uclm.es>
Description: Estimation and inference of spatial and spatio-temporal semiparametric models including spatial or spatio-temporal non-parametric trends, parametric and non-parametric covariates and, possibly, a spatial lag for the dependent variable and temporal correlation in the noise. The spatio-temporal trend can be decomposed in ANOVA way including main and interaction functional terms. Use of SAP algorithm to estimate the spatial or spatio-temporal trend and non-parametric covariates. The methodology of these models can be found in next references Basile, R. et al. (2014), <doi:10.1016/j.jedc.2014.06.011>; Rodriguez-Alvarez, M.X. et al. (2015) <doi:10.1007/s11222-014-9464-2> and, particularly referred to the focus of the package, Minguez, R., Basile, R. and Durban, M. (2020) <doi:10.1007/s10260-019-00492-8>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1), methods (>= 4.1), stats (>= 4.1), graphics (>= 4.1)
Imports: AmesHousing (>= 0.0.4), dbscan (>= 1.1-10), dplyr (>= 1.0.8), fields (>= 13.3), ggplot2 (>= 3.3.5), grDevices (>= 4.1.2), MBA (>= 0.0-9), MASS (>= 7.3-54), minqa (>= 1.2.4), Matrix (>= 1.3-4), numDeriv (>= 2016.8-1.1), plm (>= 2.6-0), rootSolve (>= 1.8.2.3), Rdpack (>= 2.1.2), sf (>= 1.0-3), spatialreg (>= 1.2-1), spdep (>= 1.1-12), splines (>= 4.1), stringr (>= 1.4.0)
Suggests: knitr (>= 1.36), rmarkdown (>= 2.11), bookdown (>= 0.24)
VignetteBuilder: knitr
URL: https://github.com/rominsal/pspatreg
BugReports: https://github.com/rominsal/pspatreg/issues
NeedsCompilation: no
Packaged: 2022-04-09 12:23:07 UTC; Roman.Minguez
Author: Roman Minguez [aut, cre] , Roberto Basile [aut] , Maria Durban [aut] , Gonzalo Espana-Heredia [aut]
Repository: CRAN
Date/Publication: 2022-04-13 08:00:02 UTC

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Package minpack.lm updated to version 1.2-2 with previous version 1.2-1 dated 2016-11-20

Title: R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds
Description: The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls-like calls using the nlsLM function.
Author: Timur V. Elzhov, Katharine M. Mullen, Andrej-Nikolai Spiess, Ben Bolker
Maintainer: Katharine M. Mullen <mullenkate@gmail.com>

Diff between minpack.lm versions 1.2-1 dated 2016-11-20 and 1.2-2 dated 2022-04-13

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New package deforestable with initial version 3.0.0
Package: deforestable
Title: Classify RGB Images into Forest or Non-Forest
Version: 3.0.0
Author: Jesper Muren [aut] , Dmitry Otryakhin [aut, cre]
Maintainer: Dmitry Otryakhin <d.otryakhin.acad@protonmail.ch>
Description: Implements two out-of box classifiers presented in <doi:10.48550/arXiv.2112.01063> for distinguishing forest and non-forest terrain images. Under these algorithms, there are frequentist approaches: one parametric, using stable distributions, and another one- non-parametric, using the squared Mahalanobis distance. The package also contains functions for data handling and building of new classifiers as well as some test data set.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: terra, jpeg, plyr, StableEstim
SystemRequirements: C++11, GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3), sqlite3
NeedsCompilation: no
Packaged: 2022-04-09 18:42:59 UTC; d
Repository: CRAN
Date/Publication: 2022-04-13 08:02:36 UTC

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New package DATAstudio with initial version 1.0
Package: DATAstudio
Version: 1.0
Date: 2022-04-02
Title: The Research Data Warehouse of Miguel de Carvalho
Description: Pulls together a collection of datasets from Miguel de Carvalho research papers. Including, - de Carvalho (2012) <doi:10.1016/j.jspi.2011.08.016>; - de Carvalho et al (2012) <doi:10.1080/03610926.2012.709905>; - de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>); - de Carvalho and Davison (2014) <doi:10.1080/01621459.2013.872651>; - de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>.
Author: Miguel de Carvalho [aut, cre]
Depends: R (>= 3.5)
Maintainer: Miguel de Carvalho <Miguel.deCarvalho@ed.ac.uk>
License: GPL (>= 3)
Repository: CRAN
Suggests: ASSA, extremis, spearmanCI, ROCnReg
Imports: scales
LazyData: true
URL: https://www.maths.ed.ac.uk/~mdecarv/
NeedsCompilation: no
Packaged: 2022-04-06 07:16:50 UTC; mdecarvalho
Date/Publication: 2022-04-13 08:42:29 UTC

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New package cheatR with initial version 1.2.1-1
Package: cheatR
Title: Catch Cheaters
Description: A set of functions to compare texts for similarity, and plot a graph of similarities among the compared texts. These functions were originally developed for detection of overlap in course hand-in.
Version: 1.2.1-1
Maintainer: Mattan S. Ben-Shachar <matanshm@post.bgu.ac.il>
URL: https://mattansb.github.io/cheatR/
BugReports: https://github.com/mattansb/cheatR/issues/
Depends: R (>= 4.0.0)
Imports: textreadr, ngram, purrr, utils, R.utils
Suggests: knitr, rmarkdown, testthat, devtools, shiny, DT, ggplot2, tidygraph, ggraph, grid
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-04-11 05:17:12 UTC; matta
Author: Mattan S. Ben-Shachar [aut, cre] , Almog Simchon [aut]
Repository: CRAN
Date/Publication: 2022-04-13 08:32:29 UTC

More information about cheatR at CRAN
Permanent link

Package UCSCXenaShiny updated to version 1.1.7 with previous version 1.1.5 dated 2022-01-15

Title: Interactive Analysis of UCSC Xena Data
Description: Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.
Author: Shixiang Wang [aut, cre] , Yi Xiong [aut] , Longfei Zhao [aut] , Kai Gu [aut] , Yin Li [aut], Fei Zhao [aut]
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaShiny versions 1.1.5 dated 2022-01-15 and 1.1.7 dated 2022-04-13

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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/NEWS.md                                                       |  106 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/GeomSplitViolin.R                                           |  110 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/analyze_gene_drug_response.R                                |  908 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/ccle.R                                                      |  288 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/data.R                                                      |  244 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/get_pancan_value.R                                          |  758 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/get_pcawg_value.R                                           |  254 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/globalVariables.R                                           |   34 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/load_data.R                                                 |  204 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/ope_pancan_value.R                                          |  122 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/query_custom_value.R                                        |   20 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/query_toil_value_df.R                                       |  122 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/run.R                                                       |   50 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/tcga_surv.R                                                 |  412 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/utils-pipe.R                                                |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/utils.R                                                     |  116 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/vis_ccle_value.R                                            |  332 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/R/xenashiny.R                                                 |   18 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/README.md                                                     |  575 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/build/vignette.rds                                            |binary
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/doc/api.R                                                |  108 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/server/global.R                                 |   32 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/server/modules.R                                |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/server/repository.R                             |  832 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/shiny-doc/citation.md                           |  108 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/shiny-doc/datasets.md                           |only
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/shiny-doc/terms.md                              |  324 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/shiny-doc/usage.md                              |  324 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/chooser.R                                    |   94 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/developers.R                                 |  244 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/footer.R                                     |   32 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/general-analysis.R                           |  188 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/global.R                                     |   22 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/help.R                                       |   70 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/home.R                                       |  284 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/pancan-analysis.R                            |  156 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/inst/shinyapp/ui/repository.R                                 |  238 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/TCGA.organ.Rd                                             |   30 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/UCSCXenaShiny.Rd                                          |   18 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/app_run.Rd                                                |   54 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/ccle_absolute.Rd                                          |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/ccle_info.Rd                                              |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/ezcor.Rd                                                  |   98 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/pcawg_info.Rd                                             |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/pcawg_purity.Rd                                           |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/pipe.Rd                                                   |   24 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/tcga_clinical.Rd                                          |   36 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/tcga_gtex.Rd                                              |   30 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/tcga_purity.Rd                                            |   36 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/tcga_surv.Rd                                              |   36 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/tcga_tmb.Rd                                               |   36 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/toil_info.Rd                                              |   36 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/vis_gene_msi_cor.Rd                                       |   66 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/vis_identifier_multi_cor.Rd                               |  146 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/man/vis_pancan_anatomy.Rd                                     |   62 
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 UCSCXenaShiny-1.1.7/UCSCXenaShiny/tests/testthat.R                                              |    8 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/tests/testthat/test-run_app.R                                 |    2 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/tests/testthat/test-vis_pancan_value.R                        |   10 
 UCSCXenaShiny-1.1.7/UCSCXenaShiny/vignettes/api.Rmd                                             |  254 
 147 files changed, 38912 insertions(+), 38827 deletions(-)

More information about UCSCXenaShiny at CRAN
Permanent link

Package stringfish updated to version 0.15.7 with previous version 0.15.5 dated 2021-12-01

Title: Alt String Implementation
Description: Provides an extendable, performant and multithreaded 'alt-string' implementation backed by 'C++' vectors and strings.
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb] , Zoltan Herczeg [ctb, cph] , University of Cambridge [cph] , Tilera Corporation [cph] , Yann Collet [ctb, cph]
Maintainer: Travers Ching <traversc@gmail.com>

Diff between stringfish versions 0.15.5 dated 2021-12-01 and 0.15.7 dated 2022-04-13

 stringfish-0.15.5/stringfish/R/RcppExportsCustom.R             |only
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 15 files changed, 150 insertions(+), 132 deletions(-)

More information about stringfish at CRAN
Permanent link

Package spooky updated to version 1.1.0 with previous version 1.0.0 dated 2022-04-12

Title: Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling
Description: Proposes application of spectral analysis and jack-knife resampling for multivariate sequence forecasting. The application allows for a fast random search in a compact space of hyper-parameters composed by Sequence Length and Jack-Knife Leave-N-Out.
Author: Giancarlo Vercellino
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>

Diff between spooky versions 1.0.0 dated 2022-04-12 and 1.1.0 dated 2022-04-13

 DESCRIPTION   |    6 ++---
 MD5           |   10 ++++-----
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More information about spooky at CRAN
Permanent link

New package RFCCA with initial version 1.0.9
Package: RFCCA
Title: Random Forest with Canonical Correlation Analysis
Version: 1.0.9
Description: Random Forest with Canonical Correlation Analysis (RFCCA) is a random forest method for estimating the canonical correlations between two sets of variables depending on the subject-related covariates. The trees are built with a splitting rule specifically designed to partition the data to maximize the canonical correlation heterogeneity between child nodes. The method is described in Alakus et al. (2021) <doi:10.1093/bioinformatics/btab158>. RFCCA uses 'randomForestSRC' package (Ishwaran and Kogalur, 2020) by freezing at the version 2.9.3. The custom splitting rule feature is utilised to apply the proposed splitting rule.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: CCA, PMA
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/calakus/RFCCA
BugReports: https://github.com/calakus/RFCCA/issues
NeedsCompilation: yes
Packaged: 2022-04-08 23:34:50 UTC; cansualakus
Author: Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb] , Udaya B. Kogalur [ctb]
Maintainer: Cansu Alakus <cansu.alakus@hec.ca>
Repository: CRAN
Date/Publication: 2022-04-13 07:52:42 UTC

More information about RFCCA at CRAN
Permanent link

Package RAMClustR updated to version 1.2.4 with previous version 1.2.3 dated 2022-03-30

Title: Mass Spectrometry Metabolomics Feature Clustering and Interpretation
Description: A feature clustering algorithm for non-targeted mass spectrometric metabolomics data. This method is compatible with gas and liquid chromatography coupled mass spectrometry, including indiscriminant tandem mass spectrometry <DOI: 10.1021/ac501530d> data.
Author: Corey D. Broeckling [aut] , Fayyaz Afsar [aut], Steffen Neumann [aut], Asa Ben-Hur [aut], Jessica Prenni [aut], Helge Hecht [cre]
Maintainer: Helge Hecht <helge.hecht@recetox.muni.cz>

Diff between RAMClustR versions 1.2.3 dated 2022-03-30 and 1.2.4 dated 2022-04-13

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More information about RAMClustR at CRAN
Permanent link

Package MAGEE updated to version 1.1.1 with previous version 1.1.0 dated 2022-03-31

Title: Mixed Model Association Test for GEne-Environment Interaction
Description: Use a 'glmmkin' class object (GMMAT package) from the null model to perform generalized linear mixed model-based single-variant and variant set main effect tests, gene-environment interaction tests, and joint tests for association, as proposed in Wang et al. (2020) <DOI:10.1002/gepi.22351>.
Author: Xinyu Wang [aut], Han Chen [aut, cre], Duy Pham [aut], Kenneth Westerman [aut], Cong Pan [aut]
Maintainer: Han Chen <han.chen.2@uth.tmc.edu>

Diff between MAGEE versions 1.1.0 dated 2022-03-31 and 1.1.1 dated 2022-04-13

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Package kequate updated to version 1.6.4 with previous version 1.6.3 dated 2020-02-07

Title: The Kernel Method of Test Equating
Description: Implements the kernel method of test equating as defined in von Davier, A. A., Holland, P. W. and Thayer, D. T. (2004) <doi:10.1007/b97446> and Andersson, B. and Wiberg, M. (2017) <doi:10.1007/s11336-016-9528-7> using the CB, EG, SG, NEAT CE/PSE and NEC designs, supporting Gaussian, logistic and uniform kernels and unsmoothed and pre-smoothed input data.
Author: Bjoern Andersson [aut, cre] , Kenny Braenberg [aut], Marie Wiberg [aut]
Maintainer: Bjoern Andersson <bjoern.h.andersson@gmail.com>

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Package immer updated to version 1.2-19 with previous version 1.1-35 dated 2018-12-10

Title: Item Response Models for Multiple Ratings
Description: Implements some item response models for multiple ratings, including the hierarchical rater model, conditional maximum likelihood estimation of linear logistic partial credit model and a wrapper function to the commercial FACETS program. See Robitzsch and Steinfeld (2018) for a description of the functionality of the package. See Wang, Su and Qiu (2014; <doi:10.1111/jedm.12045>) for an overview of modeling alternatives.
Author: Alexander Robitzsch [aut, cre], Jan Steinfeld [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package IFAA updated to version 1.0.6 with previous version 1.0.5 dated 2022-03-10

Title: Robust Inference for Absolute Abundance in Microbiome Analysis
Description: IFAA is a robust approach to make inference on the association of covariates with the absolute abundance (AA) of microbiome in an ecosystem. It can be also directly applied to relative abundance (RA) data to make inference on AA because the ratio of two RA is equal ratio of their AA. This algorithm can estimate and test the associations of interest while adjusting for potential confounders. High-dimensional covariates are handled with regularization. The estimates of this method have easy interpretation like a typical regression analysis. High-dimensional covariates are handled with regularization and it is implemented by parallel computing. False discovery rate is automatically controlled by this approach. Zeros do not need to be imputed by a positive value for the analysis. The IFAA package also offers the 'MZILN' function for estimating and testing associations of abundance ratios with covariates.
Author: Quran Wu [aut], Zhigang Li [aut, cre]
Maintainer: Zhigang Li <zhigang.li@ufl.edu>

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Package crossrun updated to version 0.1.1 with previous version 0.1.0 dated 2018-10-08

Title: Joint Distribution of Number of Crossings and Longest Run
Description: Joint distribution of number of crossings and the longest run in a series of independent Bernoulli trials. The computations uses an iterative procedure where computations are based on results from shorter series. The procedure conditions on the start value and partitions by further conditioning on the position of the first crossing (or none).
Author: Tore Wentzel-Larsen [aut, cre], Jacob Anhoej [aut]
Maintainer: Tore Wentzel-Larsen <tore.wentzellarsen@gmail.com>

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Package BiDAG updated to version 2.0.5 with previous version 2.0.4 dated 2021-11-30

Title: Bayesian Inference for Directed Acyclic Graphs
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. References: J. Kuipers, P. Suter, G. Moffa (2022) <doi:10.1080/10618600.2021.2020127>, N. Friedman and D. Koller (2003) <doi:10.1023/A:1020249912095>, D. Geiger and D. Heckerman (2002) <doi:10.1214/aos/1035844981>, J. Kuipers and G. Moffa (2017) <doi:10.1080/01621459.2015.1133426>, M. Kalisch et al. (2012) <doi:10.18637/jss.v047.i11>.
Author: Polina Suter [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Suter <polina.suter@bsse.ethz.ch>

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Package yorkr updated to version 0.0.33 with previous version 0.0.32 dated 2022-04-01

Title: Analyze Cricket Performances Based on Data from Cricsheet
Description: Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.
Author: Tinniam V Ganesh
Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

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Package QuantTools (with last version 0.5.7.1) was removed from CRAN

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

2020-10-14 0.5.7.1
2018-03-18 0.5.7
2017-09-19 0.5.6
2017-05-19 0.5.5
2017-02-26 0.5.4
2016-12-09 0.5.3
2016-12-08 0.5.2
2016-11-13 0.5.1
2016-10-13 0.5.0

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Package Allspice updated to version 1.0.4 with previous version 1.0.3 dated 2022-02-22

Title: RNA-Seq Profile Classifier
Description: We developed a lightweight machine learning tool for RNA profiling of acute lymphoblastic leukemia (ALL), however, it can be used for any problem where multiple classes need to be identified from multi-dimensional data. The methodology is described in Makinen V-P, Rehn J, Breen J, Yeung D, White DL (2022) Multi-cohort transcriptomic subtyping of B-cell acute lymphoblastic leukemia, medRxiv, <doi:10.1101/2022.02.17.22270919>. The classifier contains optimized mean profiles of the classes (centroids) as observed in the training data, and new samples are matched to these centroids using the shortest Euclidean distance. Centroids derived from a dataset of 1,598 ALL patients are included, but users can train the models with their own data as well. The output includes both numerical and visual presentations of the classification results. Samples with mixed features from multiple classes or atypical values are also identified.
Author: Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>

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