Wed, 13 Jun 2018

Package spsurvey updated to version 3.4 with previous version 3.3 dated 2016-08-19

Title: Spatial Survey Design and Analysis
Description: This group of functions implements algorithms for design and analysis of probability surveys. The functions are tailored for Generalized Random Tessellation Stratified survey designs.
Author: Tom Kincaid [aut, cre], Tony Olsen [aut], Don Stevens [ctb], Christian Platt [ctb], Denis White [ctb], Richard Remington [ctb]
Maintainer: Tom Kincaid <Kincaid.Tom@epa.gov>

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Package mboost updated to version 2.9-0 with previous version 2.8-1 dated 2017-07-23

Title: Model-Based Boosting
Description: Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.
Author: Torsten Hothorn [aut] (<https://orcid.org/0000-0001-8301-0471>), Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre] (<https://orcid.org/0000-0003-2810-3186>), Fabian Sobotka [ctb], Fabian Scheipl [ctb], Andreas Mayr [ctb]
Maintainer: Benjamin Hofner <benjamin.hofner@pei.de>

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Package driftR updated to version 1.1.0 with previous version 1.0.0 dated 2017-12-18

Title: Drift Correcting Water Quality Data
Description: A tidy implementation of equations that correct for instrumental drift in continuous water quality monitoring data. There are many sources of water quality data including private (ex: YSI instruments) and open source (ex: USGS and NDBC), each of which are susceptible to errors/inaccuracies due to drift. This package allows the user to correct their data using one or two standard reference values in a uniform, reproducible way. The equations implemented are from Hasenmueller (2011) <doi:10.7936/K7N014KS>.
Author: Andrew Shaughnessy [aut, cre], Christopher Prener [aut], Elizabeth Hasenmueller [aut]
Maintainer: Andrew Shaughnessy <andrew.shaughnessy@slu.edu>

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Package cubature updated to version 1.4 with previous version 1.3-13 dated 2018-06-11

Title: Adaptive Multivariate Integration over Hypercubes
Description: R wrapper around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes. This version provides both hcubature and pcubature routines in addition to a vector interface that results in substantial speed gains.
Author: Balasubramanian Narasimhan [aut, cre], Manuel Koller [ctb], Steven G. Johnson [aut]
Maintainer: Balasubramanian Narasimhan <naras@stat.stanford.edu>

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Package sensitivitymv updated to version 1.4.3 with previous version 1.3 dated 2015-08-19

Title: Sensitivity Analysis in Observational Studies
Description: The package performs a sensitivity analysis in an observational study using an M-statistic, for instance, the mean. The main function in the package is senmv(), but amplify() and truncatedP() are also useful. The method is developed in Rosenbaum Biometrics, 2007, 63, 456-464, <doi:10.1111/j.1541-0420.2006.00717.x>.
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>

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Package PCRedux updated to version 0.2.6-1 with previous version 0.2.6 dated 2018-05-14

Title: Quantitative Polymerase Chain Reaction (qPCR) Data Mining and Machine Learning Helper Tool
Description: Extracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) (Pabinger, Stephan, Stefan Roediger, Albert Kriegner, Klemens Vierlinger, and Andreas Weinhauusel (2014) <doi:10.1016/j.bdq.2014.08.002>) for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.
Author: Stefan Roediger [cre, aut], Michal Burdukiewicz [aut], Andrej-Nikolai Spiess [aut], Konstantin A. Blagodatskikh [aut]
Maintainer: Stefan Roediger <stefan.roediger@b-tu.de>

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Package IATanalytics updated to version 0.1.1 with previous version 0.1.0 dated 2018-05-22

Title: Compute Effect Sizes and Reliability for Implicit Association Test (IAT) Data
Description: Quickly score raw data outputted from an Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) <doi:10.1037/0022-3514.74.6.1464>. IAT scores are calculated as specified by Greenwald, Nosek, and Banaji (2003) <doi:10.1037/0022-3514.85.2.197>. The output of this function is a data frame that consists of four rows containing the following information: (1) the overall IAT effect size for the participant's dataset, (2) the effect size calculated for odd trials only, (3) the effect size calculated for even trials only, and (4) the proportion of trials with reaction times under 300ms (which is important for exclusion purposes). Items (2) and (3) allow for a measure of the internal consistency of the IAT. Specifically, you can use the subsetted IAT effect sizes for odd and even trials to calculate Cronbach's alpha across participants in the sample. The input function consists of three arguments. First, indicate the name of the dataset to be analyzed. This is the only required input. Second, indicate the number of trials in your entire IAT (the default is set to 220, which is typical for most IATs). Last, indicate whether congruent trials (e.g., flowers and pleasant) or incongruent trials (e.g., guns and pleasant) were presented first for this participant (the default is set to congruent). Data files should consist of six columns organized in order as follows: Block (0-6), trial (0-19 for training blocks, 0-39 for test blocks), category (dependent on your IAT), the type of item within that category (dependent on your IAT), a dummy variable indicating whether the participant was correct or incorrect on that trial (0=correct, 1=incorrect), and the participant’s reaction time (in milliseconds). A sample dataset (titled 'sampledata') is included in this package to practice with.
Author: Daniel Storage [aut, cre]
Maintainer: Daniel Storage <danielstorage@icloud.com>

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New package dextergui with initial version 0.1.3
Package: dextergui
Type: Package
Title: A Graphic User Interface to Dexter
Version: 0.1.3
Author: Jesse Koops, Eva de Schipper, Ivailo Partchev, Timo Bechger, Gunter Maris
Maintainer: jesse koops <jesse.koops@cito.nl>
Description: A graphical user interface for dexter. Offers Classical Test and Item analysis, Item Response analysis and data management for educational and psychological tests.
License: GPL-3
BugReports: https://github.com/jessekps/dexter/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3), dexter (>= 0.7.0)
Imports: shiny (>= 1.0.5), shinyBS, DT, htmltools, htmlwidgets, shinyjs (>= 1.0), shinyFiles, jsonlite, dplyr, tidyr, tibble, rlang, RCurl, DBI, readxl, writexl, readODS, igraph, ggplot2, ggExtra, ggridges, networkD3, Cairo, RColorBrewer, graphics, grDevices, methods, utils, tools
RoxygenNote: 6.0.1
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-13 13:01:52 UTC; jessek
Repository: CRAN
Date/Publication: 2018-06-13 21:37:58 UTC

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Package beanz updated to version 2.3 with previous version 2.2 dated 2018-04-25

Title: Bayesian Analysis of Heterogeneous Treatment Effect
Description: It is vital to assess the heterogeneity of treatment effects (HTE) when making health care decisions for an individual patient or a group of patients. Nevertheless, it remains challenging to evaluate HTE based on information collected from clinical studies that are often designed and conducted to evaluate the efficacy of a treatment for the overall population. The Bayesian framework offers a principled and flexible approach to estimate and compare treatment effects across subgroups of patients defined by their characteristics. This package allows users to explore a wide range of Bayesian HTE analysis models, and produce posterior inferences about HTE. See Wang et al. (2018) <10.18637/jss.v085.i07> for further details.
Author: Chenguang Wang [aut, cre], Ravi Varadhan [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R)
Maintainer: Chenguang Wang <cwang68@jhmi.edu>

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Package ROpenDota updated to version 0.1.2 with previous version 0.1.1 dated 2017-05-16

Title: Access OpenDota Services in R
Description: Provides a client for the API of OpenDota. OpenDota is a web service which is provide DOTA2 real time data. Data is collected through the Steam WebAPI. With ROpenDota you can easily grab the latest DOTA2 statistics in R programming such as latest match on official international competition, analyzing your or enemy performance to learn their strategies,etc. Please see <https://github.com/rosdyana/ROpenDota> for more information.
Author: Rosdyana Kusuma [aut, cre]
Maintainer: Rosdyana Kusuma <rosdyana.kusuma@gmail.com>

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Package dlm updated to version 1.1-5 with previous version 1.1-4 dated 2014-09-16

Title: Bayesian and Likelihood Analysis of Dynamic Linear Models
Description: Provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.
Author: Giovanni Petris [aut, cre], Wally Gilks [ctb] (Author of original C code for ARMS)
Maintainer: Giovanni Petris <GPetris@uark.edu>

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Package RcmdrPlugin.UCA updated to version 4.2-4 with previous version 4.1-4 dated 2018-04-09

Title: UCA Rcmdr Plug-in
Description: Some extensions to Rcmdr (R Commander), randomness test, variance test for one normal sample and predictions using active model, made by R-UCA project and used in teaching statistics at University of Cadiz (UCA).
Author: Manuel Munoz-Marquez <manuel.munoz@uca.es>
Maintainer: Manuel Munoz-Marquez <manuel.munoz@uca.es>

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Package PAS updated to version 1.2.5 with previous version 1.2 dated 2013-08-13

Title: Polygenic Analysis System (PAS)
Description: An R package for polygenic trait analysis.
Author: Zhiqiu Hu; Shizhong Xu; Zhiquan Wang; Rongcai Yang
Maintainer: Zhiqiu Hu <zhiqiu.hu@gmail.com>

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Package ShortForm updated to version 0.4.1 with previous version 0.4.0 dated 2018-03-30

Title: Automatic Short Form Creation
Description: Performs automatic creation of short forms of scales with an ant colony optimization algorithm and a Tabu search. As implemented in the package, the ant colony algorithm randomly selects items to build a model of a specified length, then updates the probability of item selection according to the fit of the best model within each set of searches. The algorithm continues until the same items are selected by multiple ants a given number of times in a row. On the other hand, the Tabu search changes one parameter at a time to be either free, constrained, or fixed while keeping track of the changes made and putting changes that result in worse fit in a "tabu" list so that the algorithm does not revisit them for some number of searches. See Leite, Huang, & Marcoulides (2008) <doi:10.1080/00273170802285743> for an applied example of the ant colony algorithm, and Marcoulides & Falk (2018) <doi:10.1080/10705511.2017.1409074> for an applied example of the Tabu search.
Author: Walter Leite [aut], Anthony Raborn [aut, cre]
Maintainer: Anthony Raborn <anthony.w.raborn@gmail.com>

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Package robeth updated to version 2.7-2 with previous version 2.7-1 dated 2018-04-18

Title: R Functions for Robust Statistics
Description: Locations problems, M-estimates of coefficients and scale in linear regression, Weights for bounded influence regression, Covariance matrix of the coefficient estimates, Asymptotic relative efficiency of regression M-estimates, Robust testing in linear models, High breakdown point regression, M-estimates of covariance matrices, M-estimates for discrete generalized linear models.
Author: Alfio Marazzi <Alfio.Marazzi@chuv.ch>
Maintainer: A. Randriamiharisoa <Alex.Randriamiharisoa@chuv.ch>

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Package bshazard updated to version 1.1 with previous version 1.0 dated 2014-02-17

Title: Nonparametric Smoothing of the Hazard Function
Description: The function estimates the hazard function non parametrically from a survival object (possibly adjusted for covariates). The smoothed estimate is based on B-splines from the perspective of generalized linear mixed models. Left truncated and right censoring data are allowed.
Author: Paola Rebora,Agus Salim, Marie Reilly
Maintainer: Paola Rebora <paola.rebora@unimib.it>

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Package BIGL updated to version 1.2.0 with previous version 1.1.1 dated 2018-01-03

Title: Biochemically Intuitive Generalized Loewe Model
Description: Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
Author: Heather Turner, Annelies Tourny, Olivier Thas, Maxim Nazarov, Rytis Bagdziunas
Maintainer: Maxim Nazarov <maxim.nazarov@openanalytics.eu>

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Package wrapr updated to version 1.5.0 with previous version 1.4.1 dated 2018-05-18

Title: Wrap R Tools for Debugging and Parametric Programming
Description: Tools for writing and debugging R code. Provides: 'let()' (converts non-standard evaluation interfaces to parametric standard evaluation interfaces), '%.>%' dot-pipe (an 'S3' configurable pipe), 'build_frame()'/'draw_frame()' ('data.frame' example tools), 'qc()' (quoting concatenate), ':=' (named map builder), 'DebugFnW()' (capture function context on error for debugging), and more.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package multimode updated to version 1.3 with previous version 1.2 dated 2018-04-27

Title: Mode Testing and Exploring
Description: Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2016 <arXiv:1609.05188>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques.
Author: Jose Ameijeiras-Alonso [aut,cre], Rosa M. Crujeiras [aut], Alberto Rodríguez-Casal [aut], The R Core Team 1996-2012 [ctb,cph] (C function 'BinDist2' obtained from package 'stats'), The R Foundation 2005 [ctb,cph] (C function 'BinDist2' obtained from package 'stats')
Maintainer: Jose Ameijeiras-Alonso <jose.ameijeiras@usc.es>

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Package sigQC updated to version 0.1.20 with previous version 0.1.14 dated 2018-04-11

Title: Quality Control Metrics for Gene Signatures
Description: Provides gene signature quality control metrics in publication ready plots. Namely, enables the visualization of properties such as expression, variability, correlation, and comparison of methods of standardisation and scoring metrics.
Author: Andrew Dhawan [aut], Alessandro Barberis [aut], Wei-Chen Cheng [aut], Francesca Buffa [aut, cre]
Maintainer: Francesca Buffa <francesca.buffa@oncology.ox.ac.uk>

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Package sae updated to version 1.2 with previous version 1.1 dated 2015-07-08

Title: Small Area Estimation
Description: Functions for small area estimation.
Author: Isabel Molina, Yolanda Marhuenda
Maintainer: Yolanda Marhuenda <y.marhuenda@umh.es>

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Package MVar.pt updated to version 2.0.2 with previous version 2.0.1 dated 2018-05-24

Title: Analise multivariada (brazilian portuguese)
Description: Pacote para analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise de cluster hierarquico e nao hierarquico, regressao linear, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

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Package cna updated to version 2.1.1 with previous version 2.1.0 dated 2018-06-01

Title: Causal Modeling with Coincidence Analysis
Description: Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>. CNA is related to Qualitative Comparative Analysis (QCA), but contrary to the latter, it is custom-built for uncovering causal structures with multiple outcomes and it builds causal models from the bottom up by gradually combining single factors to complex dependency structures until the requested thresholds of model fit are met. The new functionalities provided by this package version include various new parameters of model fit, as exhaustiveness and faithfulness, and a test for structural redundancies in multi-outcome models with a corresponding function that eliminates such redundancies. Also, the algorithmic efficiency has been significantly increased. Finally, the package now comes with an extensive vignette.
Author: Mathias Ambuehl [aut, cre, cph], Michael Baumgartner [aut, cph], Ruedi Epple [ctb], Alrik Thiem [ctb]
Maintainer: Mathias Ambuehl <mathias.ambuehl@consultag.ch>

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Package iTOP updated to version 1.0.2 with previous version 1.0.1 dated 2018-04-04

Title: Inferring the Topology of Omics Data
Description: Infers a topology of relationships between different datasets, such as multi-omics and phenotypic data recorded on the same samples. We based this methodology on the RV coefficient (Robert & Escoufier, 1976, <doi:10.2307/2347233>), a measure of matrix correlation, which we have extended for partial matrix correlations and binary data (Aben et al., 2018, <doi:10.1101/293993>).
Author: Nanne Aben
Maintainer: Nanne Aben <nanne.aben@gmail.com>

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Package dynRB updated to version 0.11 with previous version 0.10 dated 2017-11-03

Title: Dynamic Range Boxes
Description: Improves the concept of multivariate range boxes, which is highly susceptible for outliers and does not consider the distribution of the data. The package uses dynamic range boxes to overcome these problems.
Author: Manuela Schreyer <manuelalarissa.schreyer@sbg.ac.at>, Wolfgang Trutschnig <Wolfgang.Trutschnig@sbg.ac.at>, Robert R. Junker <Robert.Junker@sbg.ac.at>, Jonas Kuppler <Jonas.Kuppler@uni-duesseldorf.de>, Arne Bathke <Arne.Bathke@sbg.ac.at>
Maintainer: Manuela Schreyer <manuelalarissa.schreyer@sbg.ac.at>

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Package DALEX updated to version 0.2.3 with previous version 0.2.2 dated 2018-05-22

Title: Descriptive mAchine Learning EXplanations
Description: Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance, but such black-box models usually lack of interpretability. DALEX package contains various explainers that help to understand the link between input variables and model output. The single_variable() explainer extracts conditional response of a model as a function of a single selected variable. It is a wrapper over packages 'pdp' and 'ALEPlot'. The single_prediction() explainer attributes parts of a model prediction to particular variables used in the model. It is a wrapper over 'breakDown' package. The variable_dropout() explainer calculates variable importance scores based on variable shuffling. All these explainers can be plotted with generic plot() function and compared across different models.
Author: Przemyslaw Biecek [aut, cre]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

Diff between DALEX versions 0.2.2 dated 2018-05-22 and 0.2.3 dated 2018-06-13

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Package CSFA updated to version 1.1.0 with previous version 1.0.0 dated 2018-05-14

Title: Connectivity Scores with Factor Analysis
Description: Applies factor analysis methodology to microarray data in order to derive connectivity scores between compounds. The package also contains an implementation of the connectivity score algorithm by Zhang and Gant (2008) <doi:10.1186/1471-2105-9-258>.
Author: Ewoud De Troyer
Maintainer: Ewoud De Troyer <ewoud.detroyer@uhasselt.be>

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Package MovieSpider (with last version 1.0) was removed from CRAN

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

2018-06-12 1.0

Permanent link
Package PKNCA updated to version 0.8.5 with previous version 0.8.4 dated 2018-01-03

Title: Perform Pharmacokinetic Non-Compartmental Analysis
Description: Compute standard Non-Compartmental Analysis (NCA) parameters and summarize them. In addition to this core work, it also provides standardized plotting routines, basic assessments for biocomparison or drug interaction, and model-based estimation routines for calculating doses to reach specific values of AUC or Cmax.
Author: Bill Denney [aut, cre], Clare Buckeridge [aut], Sridhar Duvvuri [ctb]
Maintainer: Bill Denney <wdenney@humanpredictions.com>

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Package CsChange updated to version 0.1.4 with previous version 0.1.3 dated 2018-01-27

Title: Testing for Change in C-Statistic
Description: Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016) <doi:10.1001/jama.2016.5951>.
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du<dgdzc@hotmail.com>

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Package tidytree updated to version 0.1.9 with previous version 0.1.8 dated 2018-04-19

Title: A Tidy Tool for Phylogenetic Tree Data Manipulation
Description: Phylogenetic tree generally contains multiple components including node, edge, branch and associated data. 'tidytree' provides an approach to convert tree object to tidy data frame as well as provides tidy interfaces to manipulate tree data.
Author: Guangchuang Yu [aut, cre, cph] (<https://orcid.org/0000-0002-6485-8781>), Bradley Jones [ctb], Zebulun Arendsee [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package PracTools updated to version 0.9 with previous version 0.8 dated 2018-01-05

Title: Tools for Designing and Weighting Survey Samples
Description: Contains functions for sample size calculation for survey samples using stratified or clustered one-, two-, and three-stage sample designs. Other functions compute variance components for multistage designs and sample sizes in two-phase designs. A number of example data sets are included.
Author: Richard Valliant, Jill A. Dever, Frauke Kreuter
Maintainer: Richard Valliant <rvallian@umd.edu>

Diff between PracTools versions 0.8 dated 2018-01-05 and 0.9 dated 2018-06-13

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