Thu, 17 Nov 2016

Package stablespec updated to version 0.2.3 with previous version 0.1.3 dated 2016-04-08

Title: Stable Specification Search in Structural Equation Models
Description: An exploratory and heuristic approach for specification search in Structural Equation Modeling. The basic idea is to subsample the original data and then search for optimal models on each subset. Optimality is defined through two objectives: model fit and parsimony. As these objectives are conflicting, we apply a multi-objective optimization methods, specifically NSGA-II, to obtain optimal models for the whole range of model complexities. From these optimal models, we consider only the relevant model specifications (structures), i.e., those that are both stable (occur frequently) and parsimonious and use those to infer a causal model.
Author: Ridho Rahmadi [aut, cre], Perry Groot [aut, ths], Tom Heskes [aut, ths]
Maintainer: Ridho Rahmadi <r.rahmadi@cs.ru.nl>

Diff between stablespec versions 0.1.3 dated 2016-04-08 and 0.2.3 dated 2016-11-17

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Package sirt updated to version 1.13-1 with previous version 1.12-2 dated 2016-07-19

Title: Supplementary Item Response Theory Models
Description: Supplementary item response theory models to complement existing functions in R, including multidimensional compensatory and noncompensatory IRT models, MCMC for hierarchical IRT models and testlet models, NOHARM, Rasch copula model, faceted and hierarchical rater models, ordinal IRT model (ISOP), DETECT statistic, local structural equation modeling (LSEM), mean and covariance structure modelling for multivariate normally distributed data.
Author: Alexander Robitzsch [aut,cre]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between sirt versions 1.12-2 dated 2016-07-19 and 1.13-1 dated 2016-11-17

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Package Rcpp updated to version 0.12.8 with previous version 0.12.7 dated 2016-09-04

Title: Seamless R and C++ Integration
Description: The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see 'citation("Rcpp")' for details on these last two.
Author: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Nathan Russell, Douglas Bates and John Chambers
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between Rcpp versions 0.12.7 dated 2016-09-04 and 0.12.8 dated 2016-11-17

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Package mlt.docreg updated to version 0.1-1 with previous version 0.1-0 dated 2016-11-10

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt.docreg versions 0.1-0 dated 2016-11-10 and 0.1-1 dated 2016-11-17

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Package IGM.MEA updated to version 0.3.4.1 with previous version 0.3.4 dated 2016-08-31

Title: IGM MEA Analysis
Description: Software tools developed by the Institute for Genomic Medicine, Columbia University, for the characterization of neuronal networks as recorded on Multi-Electrode Arrays (MEAs).
Author: Quanli Wang, Sahar Gelfman, Diana Hall, Ryan Dhindsa
Maintainer: Sahar Gelfman <sg3261@columbia.edu>

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Package hit updated to version 0.4.0 with previous version 0.3.1 dated 2016-09-15

Title: Hierarchical Inference Testing
Description: Hierarchical inference testing (HIT) for (generalized) linear models with correlated covariates applicable to high-dimensional settings.
Author: Jonas Klasen [aut, cre]
Maintainer: Jonas Klasen <qtcat@gmx.de>

Diff between hit versions 0.3.1 dated 2016-09-15 and 0.4.0 dated 2016-11-17

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Package forecastSNSTS updated to version 1.1-0 with previous version 1.0-0 dated 2016-11-11

Title: Forecasting for Stationary and Non-Stationary Time Series
Description: Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared prediction errors for the resulting predictors. Also, functions to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series, and to verify an assumption from a paper by the authors.
Author: Tobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut]
Maintainer: Tobias Kley <t.kley@lse.ac.uk>

Diff between forecastSNSTS versions 1.0-0 dated 2016-11-11 and 1.1-0 dated 2016-11-17

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Package EFS updated to version 1.0.1 with previous version 1.0.0 dated 2016-08-02

Title: Tool for Ensemble Feature Selection
Description: Provides a function to check the importance of a feature based on a dependent classification variable. An ensemble of feature selection methods is used to determine the normalized importance value of all features. Combining these methods in one function (building the cumulative importance values) provides a stable feature selection tool. This selection can also be viewed in a barplot using the barplot_fs() function and proved using the evaluation function efs_eval().
Author: Nikita Genze, Ursula Neumann
Maintainer: Ursula Neumann <u.neumann@wz-straubing.de>

Diff between EFS versions 1.0.0 dated 2016-08-02 and 1.0.1 dated 2016-11-17

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New package DGCA with initial version 1.0.1
Package: DGCA
Title: Differential Gene Correlation Analysis
Description: Performs differential correlation analysis on input matrices, with multiple conditions specified by a design matrix. Contains functions to filter, process, save, visualize, and interpret differential correlations of identifier-pairs across the entire identifier space, or with respect to a particular set of identifiers (e.g., one). Also contains several functions to perform differential correlation analysis on clusters (i.e., modules) or genes. Finally, it contains functions to generate empirical p-values for the hypothesis tests and adjust them for multiple comparisons. Although the package was built with gene expression data in mind, it is applicable to other types of genomics data as well, in addition to being potentially applicable to data from other fields entirely. It is described more fully in the manuscript introducing it, freely available at <doi:10.1186/s12918-016-0349-1>.
Version: 1.0.1
Author: Bin Zhang [aut], Andrew McKenzie [aut, cre]
Maintainer: Andrew McKenzie <amckenz@gmail.com>
Depends: R (>= 3.2)
Imports: WGCNA, matrixStats, methods
Suggests: knitr, impute, gplots, fdrtool, testthat, ggplot2, plotrix, GOstats, HGNChelper, org.Hs.eg.db, AnnotationDbi, abind, MEGENA, Matrix, doMC, igraph, cowplot, stats, utils
VignetteBuilder: knitr
RoxygenNote: 5.0.1
License: GPL-3
LazyData: true
NeedsCompilation: no
Packaged: 2016-11-17 15:51:18 UTC; amckenz
Repository: CRAN
Date/Publication: 2016-11-17 18:33:47

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Package surveillance updated to version 1.12.2 with previous version 1.12.1 dated 2016-05-18

Title: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena
Description: Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of H÷hle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available monitoring procedures is given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. For the retrospective analysis of epidemic spread, the package provides three endemic-epidemic modeling frameworks with tools for visualization, likelihood inference, and simulation. 'hhh4' estimates models for (multivariate) count time series following Paul and Held (2011) <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>. 'twinSIR' models the susceptible-infectious-recovered (SIR) event history of a fixed population, e.g, epidemics across farms or networks, as a multivariate point process as proposed by H÷hle (2009) <doi:10.1002/bimj.200900050>. 'twinstim' estimates self-exciting point process models for a spatio-temporal point pattern of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed by Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>. A recent overview of the implemented space-time modeling frameworks for epidemic phenomena is given by Meyer et al. (2015) <http://arxiv.org/abs/1411.0416>.
Author: Michael H÷hle [aut, ths], Sebastian Meyer [aut, cre], Michaela Paul [aut], Leonhard Held [ctb, ths], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Andrea Riebler [ctb], Daniel SabanÚs BovÚ [ctb], MaŰlle Salmon [ctb], Dirk Schumacher [ctb], Stefan Steiner [ctb], Mikko Virtanen [ctb], Wei Wei [ctb], Valentin Wimmer [ctb], R Core Team [ctb] (A few code segments are modified versions of code from base R)
Maintainer: Sebastian Meyer <seb.meyer@fau.de>

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Package R2BayesX updated to version 1.1-0 with previous version 1.0-0 dated 2015-01-26

Title: Estimate Structured Additive Regression Models with 'BayesX'
Description: An R interface to estimate structured additive regression (STAR) models with 'BayesX'.
Author: Nikolaus Umlauf [aut, cre], Thomas Kneib [aut], Stefan Lang [aut], Achim Zeileis [aut]
Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at>

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Package hydrostats updated to version 0.2.5 with previous version 0.2.4 dated 2015-10-18

Title: Hydrologic Indices for Daily Time Series Data
Description: Calculates a suite of hydrologic indices for daily time series data that are widely used in hydrology and stream ecology.
Author: Nick Bond
Maintainer: Nick Bond <n.bond@latrobe.edu.au>

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Package Factoshiny updated to version 1.0.5 with previous version 1.0.4 dated 2016-06-23

Title: Perform Factorial Analysis from 'FactoMineR' with a Shiny Application
Description: Perform factorial analysis with a menu and draw graphs interactively thanks to 'FactoMineR' and a Shiny application.
Author: Pauline Vaissie, Astrid Monge, Francois Husson
Maintainer: Francois Husson <husson@agrocampus-ouest.fr>

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Package FactoMineR updated to version 1.34 with previous version 1.33 dated 2016-05-18

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis.
Author: Francois Husson, Julie Josse, Sebastien Le, Jeremy Mazet
Maintainer: Francois Husson <francois.husson@agrocampus-ouest.fr>

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Package bsam updated to version 1.1.1 with previous version 1.1.0 dated 2016-11-01

Title: Bayesian State-Space Models for Animal Movement
Description: Tools to fit Bayesian state-space models to animal tracking data. Models are provided for location filtering, location filtering and behavioural state estimation, and their hierarchical versions. The models are primarily intended for fitting to ARGOS satellite tracking data but options exist to fit to other tracking data types. For Global Positioning System data, consider the 'moveHMM' package. Simplified Markov Chain Monte Carlo convergence diagnostic plotting is provided but users are encouraged to explore tools available in packages such as 'coda' and 'boa'.
Author: Ian Jonsen [aut, cre], Sophie Bestley [ctb], Simon Wotherspoon [ctb], Michael Sumner [ctb]
Maintainer: Ian Jonsen <ian.jonsen@mq.edu.au>

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New package bcROCsurface with initial version 1.0-1
Package: bcROCsurface
Version: 1.0-1
Date: 2016-11-16
Title: Bias-Corrected Methods for Estimating the ROC Surface of Continuous Diagnostic Tests
Author: Khanh To Duc, with contributions from Monica Chiogna and Gianfranco Adimari
Maintainer: Khanh To Duc <toduc@stat.unipd.it>
Description: The bias-corrected estimation methods for the receiver operating characteristics ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) assumption.
License: GPL (>= 2)
Depends: R(>= 2.15.0), nnet, rgl, boot, stats, utils, graphics, parallel
Imports: Rcpp (>= 0.12.2)
LinkingTo: Rcpp, RcppArmadillo
LazyLoad: yes
LazyData: TRUE
ByteCompile: yes
RoxygenNote: 5.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2016-11-17 10:12:37 UTC; duckhanh
Repository: CRAN
Date/Publication: 2016-11-17 14:34:33

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Package biogas updated to version 1.5.0 with previous version 1.4.0 dated 2016-05-24

Title: Process Biogas Data and Predict Biogas Production
Description: Functions for working with biogas data. Both low- and high-level functions are included for carrying out common tasks for analysis of biogas and related data. Molar mass and calculated oxygen demand (COD') can be determined from a chemical formula. Measured gas volume can be corrected for water vapor and to (possibly user-defined) standard temperature and pressure. Gas composition, cumulative production, or other variables can be interpolated to a specified time. Cumulative biogas and methane production (and rates) can be calculated using volumetric, manometric, or gravimetric methods for any number of reactors. With cumulative methane production data and data on reactor contents, biochemical methane potential (BMP) can be calculated and summarized, including subtraction of the inoculum contribution and normalization by substrate mass. Cumulative production and production rates can be summarized in several different ways (e.g., omitting normalization) using the same function. Lastly, biogas and methane production can be predicted from substrate composition and additional, optional data.
Author: Sasha D. Hafner [aut, cre], Charlotte Rennuit [aut], Jin Mi Triolo [ctb], Ali Heidarzadeh Vazifehkhoran [ctb]
Maintainer: Sasha D. Hafner <saha@kbm.sdu.dk>

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Package ABCoptim updated to version 0.14.0 with previous version 0.13.11 dated 2013-11-06

Title: Implementation of Artificial Bee Colony (ABC) Optimization
Description: An implementation of Karaboga (2005) Artificial Bee Colony Optimization algorithm <http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf>. This (working) version is a Work-in-progress, which is why it has been implemented using pure R code. This was developed upon the basic version programmed in C and distributed at the algorithm's official website.
Author: George Vega Yon [aut, cre], Enyelbert Mu├▒oz [ctb]
Maintainer: George Vega Yon <g.vegayon@gmail.com>

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Package udunits2 updated to version 0.13 with previous version 0.11 dated 2016-07-22

Title: Udunits-2 Bindings for R
Description: Provides simple bindings to Unidata's udunits library.
Author: James Hiebert <hiebert@uvic.ca>
Maintainer: James Hiebert <hiebert@uvic.ca>

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New package tinsel with initial version 0.0.1
Package: tinsel
Title: Transform Functions using Decorators
Version: 0.0.1
Authors@R: person("Nathan", "Teetor", email = "nathanteetor@gmail.com", role = c("aut", "cre"))
Description: Instead of nesting function calls, annotate and transform functions using "#." comments.
License: MIT + file LICENSE
URL: https://github.com/nteetor/tinsel
BugReports: https://github.com/nteetor/tinsel/issues
Encoding: UTF-8
RoxygenNote: 5.0.1
Depends: R (>= 3.3.1)
Suggests: testthat, rstudioapi
NeedsCompilation: no
Packaged: 2016-11-16 18:07:32 UTC; nathanteetor
Author: Nathan Teetor [aut, cre]
Maintainer: Nathan Teetor <nathanteetor@gmail.com>
Repository: CRAN
Date/Publication: 2016-11-17 08:27:54

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Package statmod updated to version 1.4.27 with previous version 1.4.26 dated 2016-08-28

Title: Statistical Modeling
Description: A collection of algorithms and functions to aid statistical modeling. Includes growth curve comparisons, limiting dilution analysis (aka ELDA), mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Includes advanced generalized linear model functions that implement secure convergence, dispersion modeling and Tweedie power-law families.
Author: Gordon Smyth [cre, aut], Yifang Hu [ctb], Peter Dunn [ctb], Belinda Phipson [ctb], Yunshun Chen [ctb]
Maintainer: Gordon Smyth <smyth@wehi.edu.au>

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Package s20x updated to version 3.1-18 with previous version 3.1-17 dated 2016-04-14

Title: Functions for University of Auckland Course STATS 201/208 Data Analysis
Description: A set of functions used in teaching STATS 201/208 Data Analysis at the University of Auckland. The functions are designed to make parts of R more accessible to a large undergraduate population who are mostly not statistics majors.
Author: Andrew Balemi, Dineika Chandra, James Curran, Brant Deppa, Mike Forster, Brendan McArdle, Chris Wild
Maintainer: James Curran <j.curran@auckland.ac.nz>

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Package rnoaa updated to version 0.6.6 with previous version 0.6.5 dated 2016-10-22

Title: 'NOAA' Weather Data from R
Description: Client for many 'NOAA' data sources including the 'NCDC' climate 'API' at <https://www.ncdc.noaa.gov/cdo-web/webservices/v2>, with functions for each of the 'API' 'endpoints': data, data categories, data sets, data types, locations, location categories, and stations. In addition, we have an interface for 'NOAA' sea ice data, the 'NOAA' severe weather inventory, 'NOAA' Historical Observing 'Metadata' Repository ('HOMR') data, 'NOAA' storm data via 'IBTrACS', tornado data via the 'NOAA' storm prediction center, and more.
Author: Scott Chamberlain [aut, cre], Brooke Anderson [ctb], Ma├źlle Salmon [ctb], Adam Erickson [ctb], Nicholas Potter [ctb], Joseph Stachelek [ctb], Alex Simmons [ctb], Karthik Ram [ctb], Hart Edmund [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between rnoaa versions 0.6.5 dated 2016-10-22 and 0.6.6 dated 2016-11-17

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New package NestedCategBayesImpute with initial version 1.0.0
Package: NestedCategBayesImpute
Type: Package
Title: Modeling and Generating Synthetic Versions of Nested Categorical Data in the Presence of Impossible Combinations
Version: 1.0.0
Date: 2016-11-16
Author: Quanli Wang, Olanrewaju Akande, Jingchen Hu, Jerry Reiter and Andres Barrientos
Maintainer: Quanli Wang <quanli@stat.duke.edu>
Description: This tool set provides a set of functions to fit the nested Dirichlet process mixture of products of multinomial distributions (NDPMPM) model for nested categorical household data in the presence of impossible combinations. It has direct applications in generating synthetic nested household data.
License: GPL (>= 3)
LazyData: TRUE
Imports: stats, coda, dplyr, Rcpp (>= 0.12.0)
LinkingTo: Rcpp
URL: https://arxiv.org/abs/1412.2282
NeedsCompilation: yes
Packaged: 2016-11-16 23:26:32 UTC; qw2192
Repository: CRAN
Date/Publication: 2016-11-17 08:27:32

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New package NegBinBetaBinreg with initial version 1.0
Package: NegBinBetaBinreg
Type: Package
Title: Negative Binomial and Beta Binomial Bayesian Regression Models
License: GPL (>= 2)
Version: 1.0
Date: 2016-11-15
Author: Edilberto Cepeda-Cuervo, Maria Victoria Cifuentes-Amado and Margarita Marin
Maintainer: Edilberto Cepeda <ecepedac@unal.edu.co>
Depends: R (>= 3.1.1), mvtnorm, Matrix, boot
Description: The Negative Binomial regression with mean and shape modeling and mean and variance modeling and Beta Binomial regression with mean and dispersion modeling.
NeedsCompilation: no
Packaged: 2016-11-15 20:15:15 UTC; margarita
Repository: CRAN
Date/Publication: 2016-11-17 08:27:30

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Package ltmle updated to version 0.9-9 with previous version 0.9-8 dated 2016-04-20

Title: Longitudinal Targeted Maximum Likelihood Estimation
Description: Targeted Maximum Likelihood Estimation (TMLE) of treatment/censoring specific mean outcome or marginal structural model for point-treatment and longitudinal data.
Author: Joshua Schwab [aut, cre], Samuel Lendle [aut], Maya Petersen [aut], Mark van der Laan [aut], Susan Gruber [ctb]
Maintainer: Joshua Schwab <joshuaschwab@yahoo.com>

Diff between ltmle versions 0.9-8 dated 2016-04-20 and 0.9-9 dated 2016-11-17

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Package KOGMWU updated to version 1.1 with previous version 1.0 dated 2015-03-05

Title: Functional Summary and Meta-Analysis of Gene Expression Data
Description: Rank-based tests for enrichment of KOG (euKaryotic Orthologous Groups) classes with up- or down-regulated genes based on a continuous measure. The meta-analysis is based on correlation of KOG delta-ranks across datasets (delta-rank is the difference between mean rank of genes belonging to a KOG class and mean rank of all other genes). With binary measure (1 or 0 to indicate significant and non-significant genes), one-tailed Fisher's exact test for over-representation of each KOG class among significant genes will be performed.
Author: Mikhail V. Matz
Maintainer: Mikhail V. Matz <matz@utexas.edu>

Diff between KOGMWU versions 1.0 dated 2015-03-05 and 1.1 dated 2016-11-17

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New package kntnr with initial version 0.4.0
Package: kntnr
Type: Package
Title: R Client for 'kintone' API
Version: 0.4.0
Date: 2016-11-17
Authors@R: person("Hiroaki", "Yutani", , "yutani.ini@gmail.com", c("aut", "cre"))
Description: Retrieve data from 'kintone' (<https://www.kintone.com/>) via its API. 'kintone' is an enterprise application platform.
License: MIT + file LICENSE
Imports: base64enc, dplyr, httr, jsonlite, lazyeval, lubridate, methods, purrr (>= 0.2), rstudioapi, stringr
Suggests: testthat, tidyr
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-11-17 00:47:21 UTC; yutani
Author: Hiroaki Yutani [aut, cre]
Maintainer: Hiroaki Yutani <yutani.ini@gmail.com>
Repository: CRAN
Date/Publication: 2016-11-17 08:27:40

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Package HDoutliers updated to version 0.12 with previous version 0.9 dated 2016-11-01

Title: Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers
Description: An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers. See <https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf>.
Author: Leland Wilkinson [aut], Chris Fraley [cre]
Maintainer: Chris Fraley <cfraley@tableau.com>

Diff between HDoutliers versions 0.9 dated 2016-11-01 and 0.12 dated 2016-11-17

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New package gwfa with initial version 0.0.4
Package: gwfa
Type: Package
Title: Geographically Weighted Fractal Analysis
Version: 0.0.4
Date: 2016-10-28
Author: Francois Semecurbe, Stephane G. Roux, and Cecile Tannier
Maintainer: Francois Semecurbe <francois.semecurbe@univ-fcomte.fr>
Description: Performs Geographically Weighted Fractal Analysis (GWFA) to calculate the local fractal dimension of a set of points. GWFA mixes the Sandbox multifractal algorithm and the Geographically Weighted Regression. Unlike fractal box-counting algorithm, the sandbox algorithm avoids border effects because the boxes are adjusted on the set of points. The Geographically Weighted approach consists in applying a kernel that describes the way the neighbourhood of each estimated point is taken into account to estimate its fractal dimension. GWFA can be used to discriminate built patterns of a city, a region, or a whole country.
Suggests: rgdal, rgeos
License: GPL (>= 2)
Imports: methods,Rcpp (>= 0.11.3),sp
LinkingTo: Rcpp
NeedsCompilation: yes
RoxygenNote: 5.0.1
Packaged: 2016-11-16 19:59:43 UTC; Fsemecurbe
Repository: CRAN
Date/Publication: 2016-11-17 08:27:38

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Package glm.predict updated to version 2.4-0 with previous version 2.3-0 dated 2016-10-06

Title: Predicted Values and Discrete Changes for GLM
Description: Functions to calculate predicted values and the difference between the two cases with confidence interval for glm(), glm.nb(), polr() and multinom().
Author: Benjamin Schlegel [aut,cre]
Maintainer: Benjamin Schlegel <kontakt@benjaminschlegel.ch>

Diff between glm.predict versions 2.3-0 dated 2016-10-06 and 2.4-0 dated 2016-11-17

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Package fcros updated to version 1.5.2 with previous version 1.5.1 dated 2016-10-10

Title: A Method to Search for Differentially Expressed Genes and to Detect Recurrent Chromosomal Copy Number Aberrations
Description: A fold change rank based method is presented to search for differentially expressed genes and to detect recurrent chromosomal copy number aberrations. This method may be useful for high-throughput biological data (microarray, sequencing, ...). Probabilities are associated with genes/probes in the dataset and there is no problem of multiple tests when using this method. For aCGH data, segmentation results are obtained by merging the significant probes detected.
Author: Doulaye Dembele
Maintainer: Doulaye Dembele <doulaye@igbmc.fr>

Diff between fcros versions 1.5.1 dated 2016-10-10 and 1.5.2 dated 2016-11-17

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