From 3874fe5f14b003fa9a67fba700f9e4737536efe5 Mon Sep 17 00:00:00 2001 From: Marco Maier Date: Thu, 28 May 2020 20:09:13 +0200 Subject: [PATCH] Version 0.0.7 for CRAN (fixed testthat files for checks on CRAN) --- DESCRIPTION | 5 +- NEWS | 3 +- README.Rmd | 10 +- README.md | 7 +- inst/NEWS.pdf | Bin 31419 -> 31434 bytes inst/doc/DirichletReg-vig-old.Rnw | 331 ---------------------- inst/doc/DirichletReg-vig-old.pdf | Bin 103408 -> 0 bytes tests/testthat.R | 1 + tests/testthat/test-ArcticTests_AltPar.R | 8 +- tests/testthat/test-ArcticTests_CommPar.R | 8 +- 10 files changed, 19 insertions(+), 354 deletions(-) delete mode 100644 inst/doc/DirichletReg-vig-old.Rnw delete mode 100644 inst/doc/DirichletReg-vig-old.pdf diff --git a/DESCRIPTION b/DESCRIPTION index 4de0532..3b2c092 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,13 +1,14 @@ Package: DirichletReg Type: Package Version: 0.7-0 -Date: 2019-11-25 +Date: 2020-05-28 Title: Dirichlet Regression in R Description: Implements Dirichlet regression models in R. Authors@R: person(given = c("Marco", "Johannes"), family = "Maier", email = "marco_maier@posteo.de", - role = c("cre", "aut")) + role = c("cre", "aut"), + comment = c(ORCID = "0000-0002-1715-7456")) Encoding: UTF-8 Depends: R (>= 3.0.0), Formula Imports: stats, graphics, methods, maxLik diff --git a/NEWS b/NEWS index 8cb2d29..550f8c2 100644 --- a/NEWS +++ b/NEWS @@ -54,9 +54,10 @@ Changes in Version 0.6-0: will fail. This will be handled automatically in subsequent releases, but for now, please remove the respective terms. If you fit a model and it says something like: - + Error in prepareFixed(start = start, activePar = NULL, fixed = fixed) : At least one parameter must not be fixed using argument 'fixed' + you most likely have collinear terms or "empty" combinations of interaction terms. diff --git a/README.Rmd b/README.Rmd index 53daea0..c19e8bf 100644 --- a/README.Rmd +++ b/README.Rmd @@ -13,11 +13,7 @@ knitr::opts_chunk$set( ``` -CRAN: [![CRAN Status](https://www.r-pkg.org/badges/version/DirichletReg)](https://cran.r-project.org/package=DirichletReg) - - -Travis-CI: [![Travis Build Status](https://travis-ci.org/maiermarco/DirichletReg.svg?branch=master)](https://travis-ci.org/maiermarco/DirichletReg) - - -Codecov: [![codecov](https://codecov.io/gh/maiermarco/DirichletReg/branch/master/graph/badge.svg)](https://codecov.io/gh/maiermarco/DirichletReg) +[![CRAN Status](https://www.r-pkg.org/badges/version/DirichletReg)](https://cran.r-project.org/package=DirichletReg) +[![Travis Build Status](https://travis-ci.org/maiermarco/DirichletReg.svg?branch=master)](https://travis-ci.org/maiermarco/DirichletReg) +[![codecov](https://codecov.io/gh/maiermarco/DirichletReg/branch/master/graph/badge.svg)](https://codecov.io/gh/maiermarco/DirichletReg) diff --git a/README.md b/README.md index 19e53fd..81a55b3 100644 --- a/README.md +++ b/README.md @@ -3,12 +3,9 @@ -CRAN: [![CRAN +[![CRAN Status](https://www.r-pkg.org/badges/version/DirichletReg)](https://cran.r-project.org/package=DirichletReg) - -Travis-CI: [![Travis Build +[![Travis Build Status](https://travis-ci.org/maiermarco/DirichletReg.svg?branch=master)](https://travis-ci.org/maiermarco/DirichletReg) - -Codecov: [![codecov](https://codecov.io/gh/maiermarco/DirichletReg/branch/master/graph/badge.svg)](https://codecov.io/gh/maiermarco/DirichletReg) diff --git a/inst/NEWS.pdf b/inst/NEWS.pdf index d8ab43090b01ad77d6d7a7d2bed2b19567ac13b5..bebe5abe900594e8bfd5b375c02a588865e3aee3 100644 GIT binary patch delta 11361 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-%\VignetteIndexEntry{DirichletReg -- Article Sources (TeX)} -\SweaveOpts{keep.source=FALSE} -<>= -options( - prompt = "> ", - continue = "+ ", - width = 100L, - encoding = "UTF-8", - useFancyQuotes = TRUE -) -library("DirichletReg") -@ -\documentclass[nojss]{jss} -\usepackage[utf8]{inputenx} -\usepackage[T1]{fontenc} - -\author{Marco J.\ Maier\\Wirtschaftsuniversit\"at Wien} -\title{\pkg{DirichletReg}: Dirichlet Regression for Compositional Data in \proglang{R}} - -\Plainauthor{Marco J. Maier} -\Plaintitle{DirichletReg: Dirichlet Regression for Compositional Data in R} - -\Abstract{\noindent Full \proglang{R} Code for\\Maier, M.\,J. (2014). DirichletReg: Dirichlet Regression for Compositional Data in R. Research Report Series\slash{}Department of Statistics and Mathematics, 125. WU Vienna University of Economics and Business, Vienna. \url{http://epub.wu.ac.at/4077/}} - -\Keywords{ - Dirichlet regression, - Dirichlet distribution, - multivariate generalized linear model, - rates, - proportions, - rates, - compositional data, - simplex, - \proglang{R}} -\Plainkeywords{ - Dirichlet regression, - Dirichlet distribution, - multivariate generalized linear model, - rates, - proportions, - rates, - compositional data, - simplex, - R} - -\Address{ - Marco J.\ Maier\\ - Institute for Statistics and Mathematics\\ - Wirtschaftsuniversit\"at Wien\\ - Vienna University of Economics and Business\\ - Augasse 2--6\\ - 1090 Vienna, Austria\\ - Telephone: +43/1/31336--4335\\ - E-mail: \email{Marco\_Maier@posteo.de}\\ - URL: \url{http://statmath.wu.ac.at/~maier/} -} - -\usepackage{amsmath,amssymb,amsfonts,bm,lmodern} -\usepackage{graphicx,tabularx,booktabs,array,blkarray,multicol} - -\newcommand{\given}{\,\vert\,} -\newcommand{\gnuR}{\proglang{R}} - -%\usepackage{Sweave} - \usepackage{xcolor} % [rgb] - \definecolor{inputblue}{HTML}{383D93} % {Hsb}{240, .8, .3} - \definecolor{outputred}{HTML}{8D1125} % {Hsb}{ 0, .8, .3} - \usepackage{fancyvrb,textcomp} - \makeatletter - \begingroup - \catcode`'=\active \catcode``=\active - \g@addto@macro\@noligs{\let`\textasciigrave \let'\textquotesingle} - \endgroup - \makeatother - \renewenvironment{Schunk}{\begingroup\footnotesize}{\endgroup} - \DefineVerbatimEnvironment{Sinput}{Verbatim}{fontshape=sl,fontsize=\footnotesize,formatcom=\color{inputblue}} - \DefineVerbatimEnvironment{Soutput}{Verbatim}{fontsize=\scriptsize,formatcom=\color{outputred}} - \DefineVerbatimEnvironment{Scode}{Verbatim}{fontshape=sl,fontsize=\footnotesize} - \setkeys{Gin}{width=0.8\textwidth,keepaspectratio=true} - -\begin{document}\setcounter{section}{3} -\section{Application examples} -\subsection{The Arctic lake (common parametrization)} -<<>>= -library("DirichletReg") -head(ArcticLake) -AL <- DR_data(ArcticLake[,1:3]) -@ -<<>>= -AL[1:6,] -@ -Code for Fig.~\ref{fig:AL.tern.compo} (left): -<>= -plot(AL, cex=.5, a2d=list(colored=FALSE, c.grid=FALSE)) -@ -Code for Fig.~\ref{fig:AL.tern.compo} (right): -<>= -plot(rep(ArcticLake$depth,3),as.numeric(AL), - pch=21, bg=rep(c("#E495A5", "#86B875", "#7DB0DD"),each=39), # colorspace : rainbow_hcl(3) - xlab="Depth (m)", ylab="Proportion", ylim=0:1) -@ -\begin{figure}\centering% -\setkeys{Gin}{width=.49\linewidth, keepaspectratio=true} -<>= -<> -@ -\hfill\setkeys{Gin}{width=.49\linewidth, keepaspectratio=true} -<>= -<> -@ -\caption{Arctic lake: Ternary plot and depth vs.\ composition.}\label{fig:AL.tern.compo} -\end{figure} -<<>>= -lake1 <- DirichReg(AL~depth, ArcticLake) -lake1 -coef(lake1) -@ -<<>>= -lake2 <- update(lake1, .~.+I(depth^2)|.+I(depth^2)|.+I(depth^2)) -anova(lake1,lake2) -@ -<<>>= -summary(lake2) -@ -Code for Fig.~\ref{fig:AL.tern.fitted}: -<>= -par(mar=c(4, 4, 4, 4)+0.1) -plot(rep(ArcticLake$depth,3),as.numeric(AL), - pch=21, bg=rep(c("#E495A5", "#86B875", "#7DB0DD"),each=39), # colorspace : rainbow_hcl(3) - xlab="Depth (m)", ylab="Proportion", ylim=0:1, main="Sediment Composition in an Arctic Lake") -Xnew <- data.frame(depth=seq(min(ArcticLake$depth), max(ArcticLake$depth), length.out=100)) -for(i in 1:3)lines(cbind(Xnew, predict(lake2, Xnew)[,i]),col=c("#E495A5", "#86B875", "#7DB0DD")[i],lwd=2) # colorspace : rainbow_hcl(3) -legend("topleft", legend=c("Sand","Silt","Clay"), lwd=2, col=c("#E495A5", "#86B875", "#7DB0DD"), pt.bg=c("#E495A5", "#86B875", "#7DB0DD"), pch=21,bty="n") # colorspace : rainbow_hcl(3) - -par(new=TRUE) -plot(cbind(Xnew, predict(lake2, Xnew, F,F,T)), lty="24", type="l",ylim=c(0,max(predict(lake2, Xnew, F,F,T))),axes=F,ann=F,lwd=2) -axis(4) -mtext(expression(paste("Precision (",phi,")",sep="")), 4, line=3) -legend("top",legend=c(expression(hat(mu[c]==hat(alpha)[c]/hat(alpha)[0])),expression(hat(phi)==hat(alpha)[0])),lty=c(1,2),lwd=c(3,2),bty="n") -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Arctic lake: Fitted values of the quadratic model.}\label{fig:AL.tern.fitted} -\end{figure} -<<>>= -AL <- ArcticLake -AL$AL <- DR_data(ArcticLake[,1:3]) - -dd <- range(ArcticLake$depth) -X <- data.frame(depth=seq(dd[1], dd[2], length.out=200)) - -pp <- predict(DirichReg(AL~depth+I(depth^2),AL), X) -@ -Code for Fig.~\ref{fig:AL.tern.fitted.two}: -<>= -plot(AL$AL, cex=.1, reset_par=FALSE) -points(toSimplex(AL$AL), pch=16, cex=.5, col=gray(.5)) - -lines(toSimplex(pp), lwd=3, col=c("#6E1D34", "#004E42")[2]) # colorspace : rainbow_hcl(2,l=25) - -Dols <- log(cbind(ArcticLake[,2]/ArcticLake[,1], - ArcticLake[,3]/ArcticLake[,1])) - -ols <- lm(Dols~depth+I(depth^2), ArcticLake) -p2 <- predict(ols, X) -p2m <- exp(cbind(0,p2[,1],p2[,2]))/rowSums(exp(cbind(0,p2[,1],p2[,2]))) - -lines(toSimplex(p2m), lwd=3, col=c("#6E1D34", "#004E42")[1], lty="21") # colorspace : rainbow_hcl(2,l=25) -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Arctic lake: OLS (dashed) vs.\ Dirichlet regression (solid) predictions.}\label{fig:AL.tern.fitted.two} -\end{figure} -\subsection{Blood samples (alternative parametrization)} -<<>>= -Bld <- BloodSamples -Bld$Smp <- DR_data(Bld[,1:4]) -@ -<<>>= -blood1 <- DirichReg(Smp~Disease|1, Bld, model="alternative", base=3) -blood2 <- DirichReg(Smp~Disease|Disease, Bld, model="alternative", base=3) -anova(blood1, blood2) -@ -<<>>= -summary(blood1) -@ -Code for Fig.~\ref{fig:blood:boxfitted}: -<>= -par(mfrow=c(1,4), mar=c(4,4,4,2)+.25) -for(i in 1:4){ - boxplot(Bld$Smp[,i]~Bld$Disease, ylim=range(Bld$Smp[,1:4]), main=paste(names(Bld)[i]), xlab="Disease Type", ylab="Proportion") - segments(c(-5,1.5),unique(fitted(blood2)[,i]), - c(1.5,5),unique(fitted(blood2)[,i]),lwd=2,lty=2) -} -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Blood samples: Box plots and fitted values (dashed lines indicate the fitted values for each group).} -\label{fig:blood:boxfitted} -\end{figure} -<<>>= -alpha <- predict(blood2, data.frame(Disease=factor(c("A","B"))), F, T, F) -L <- sapply(1:2, function(i) ddirichlet(DR_data(Bld[31:36,1:4]), unlist(alpha[i,]))) -LP <- L / rowSums(L) -dimnames(LP) <- list(paste("C",1:6), c("A", "B")) -print(data.frame(round(LP * 100, 1),"pred."=as.factor(ifelse(LP[,1]>LP[,2], "==> A", "==> B"))),print.gap=2) -@ -Code for Fig.~\ref{fig:blood:predictions}: -<>= -B2 <- DR_data(BloodSamples[,c(1,2,4)]) -plot(B2, cex=.001, reset_par=FALSE) - -div.col <- colorRampPalette(c("#023FA5", "#c0c0c0", "#8E063B"))(100) -# expected values -temp <- (alpha/rowSums(alpha))[,c(1,2,4)] -points(toSimplex(temp/rowSums(temp)), pch=22, bg=div.col[c(1,100)], cex=2, lwd=.25) -# known values -temp <- B2[1:30,] -points(toSimplex(temp/rowSums(temp)), pch=21, bg=(div.col[c(1,100)])[BloodSamples$Disease[1:30]], cex=.5, lwd=.25) -# unclassified -temp <- B2[31:36,] -points(toSimplex(temp/rowSums(temp)), pch=21, bg=div.col[round(100*LP[,2],0)], cex=1, lwd=.5) - -legend("topright", bty="n", legend=c("Disease A","Disease B",NA,"Expected Values"), pch=c(21,21,NA,22), pt.bg=c(div.col[c(1,100)],NA,"white")) -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Blood samples: Observed values and predictions} -\label{fig:blood:predictions} -\end{figure} -\subsection{Reading skills data (alternative parametrization)} -<<>>= -RS <- ReadingSkills -RS$acc <- DR_data(RS$accuracy) - -RS$dyslexia <- C(RS$dyslexia, treatment) -rs1 <- DirichReg(acc ~ dyslexia*iq | dyslexia*iq, RS, model="alternative") -rs2 <- DirichReg(acc ~ dyslexia*iq | dyslexia+iq, RS, model="alternative") -anova(rs1,rs2) -@ -Code for Fig.~\ref{fig:ReadingSkills}: -<>= -g.ind <- as.numeric(RS$dyslexia) -g1 <- g.ind == 1 # normal -g2 <- g.ind != 1 # dyslexia -par(mar=c(4,4,4,4)+0.25) -plot(accuracy~iq, RS, pch=21, bg=c("#E495A5", "#39BEB1")[3-g.ind], # colorspace : rainbow_hcl(2) -cex=1.5, main="Dyslexic (Red) vs. Control (Green) Group", -xlab="IQ Score",ylab="Reading Accuracy", xlim=range(ReadingSkills$iq)) - -x1 <- seq(min(RS$iq[g1]), max(RS$iq[g1]), length.out=200) -x2 <- seq(min(RS$iq[g2]), max(RS$iq[g2]), length.out=200) -n <- length(x1) -X <- data.frame(dyslexia=factor(rep(0:1, each=n), levels=0:1, labels=c("no", "yes")),iq=c(x1,x2)) -pv <- predict(rs2, X, TRUE, TRUE, TRUE) - -lines(x1, pv$mu[1:n,2], col=c("#E495A5", "#39BEB1")[2],lwd=3) # colorspace : rainbow_hcl(2) -lines(x2, pv$mu[(n+1):(2*n),2], col=c("#E495A5", "#39BEB1")[1],lwd=3) # colorspace : rainbow_hcl(2) - -a <- RS$accuracy -logRa_a <- log(a/(1-a)) -rlr <- lm(logRa_a~dyslexia*iq, RS) -ols <- 1/(1+exp(-predict(rlr, X))) -lines(x1, ols[1:n], col=c("#AD6071", "#00897D")[2],lwd=3,lty=2) # colorspace : rainbow_hcl(2,l=50) -lines(x2, ols[(n+1):(2*n)], col=c("#AD6071", "#00897D")[1],lwd=3,lty=2) # colorspace : rainbow_hcl(2,l=50) - -### precision plot -par(new=TRUE) -plot(x1, pv$phi[1:n], col=c("#6E1D34", "#004E42")[2], lty="11", type="l",ylim=c(0,max(pv$phi)),axes=F,ann=F,lwd=2, xlim=range(RS$iq)) # colorspace : rainbow_hcl(2,l=25) -lines(x2, pv$phi[(n+1):(2*n)], col=c("#6E1D34", "#004E42")[1], lty="11", type="l",lwd=2) # colorspace : rainbow_hcl(2,l=25) -axis(4) -mtext(expression(paste("Precision (",phi,")",sep="")), 4, line=3) -legend("topleft",legend=c(expression(hat(mu)),expression(hat(phi)),"OLS"),lty=c(1,3,2),lwd=c(3,2,3),bty="n") -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Reading skills: Predicted values of Dirichlet regression and OLS regression.}\label{fig:ReadingSkills} -\end{figure} -<<>>= -a <- RS$accuracy -logRa_a <- log(a/(1-a)) -rlr <- lm(logRa_a~dyslexia*iq, RS) -summary(rlr) -@ -<<>>= -summary(rs2) -@ -<<>>= -confint(rs2) -confint(rs2, exp=TRUE) -@ -Code for Fig.~\ref{fig:readingskills.residplot}: -<>= -gcol <- c("#E495A5", "#39BEB1")[3-as.numeric(RS$dyslexia)] # colorspace : rainbow_hcl(2) -tmt <- c(-3,3) -par(mfrow=c(3,2), cex=.8) -qqnorm(residuals(rlr,"pearson"), ylim=tmt, xlim=tmt, pch=21, bg=gcol, main="Normal Q-Q-Plot: OLS Residuals",cex=.75,lwd=.5) -abline(0,1, lwd=2) -qqline(residuals(rlr,"pearson"), lty=2) - -qqnorm(residuals(rs2,"standardized")[,2], ylim=tmt, xlim=tmt, pch=21, bg=gcol, main="Normal Q-Q-Plot: DirichReg Residuals",cex=.75,lwd=.5) -abline(0,1, lwd=2) -qqline(residuals(rs2,"standardized")[,2], lty=2) - -plot(ReadingSkills$iq, residuals(rlr,"pearson"), pch=21, bg=gcol, ylim=c(-3,3),main="OLS Residuals",xlab="IQ",ylab="Pearson Residuals",cex=.75,lwd=.5) -abline(h=0,lty=2) -plot(ReadingSkills$iq, residuals(rs2,"standardized")[,2], pch=21, bg=gcol ,ylim=c(-3,3),main="DirichReg Residuals",xlab="IQ",ylab="Standardized Residuals",cex=.75,lwd=.5) -abline(h=0,lty=2) - -plot(fitted(rlr), residuals(rlr,"pearson"), pch=21, bg=gcol ,ylim=c(-3,3),main="OLS Residuals",xlab="Fitted",ylab="Pearson Residuals",cex=.75,lwd=.5) -abline(h=0,lty=2) -plot(fitted(rs2)[,2], residuals(rs2,"standardized")[,2], pch=21, bg=gcol ,ylim=c(-3,3),main="DirichReg Residuals",xlab="Fitted",ylab="Standardized Residuals",cex=.75,lwd=.5) -abline(h=0,lty=2) -@ -\begin{figure}\centering% -<>= -<> -@ -\caption{Reading skills: residual plots of OLS and Dirichlet regression models.}\label{fig:readingskills.residplot} -\end{figure} -\end{document} diff --git a/inst/doc/DirichletReg-vig-old.pdf b/inst/doc/DirichletReg-vig-old.pdf deleted file mode 100644 index 1a3c9f6cd46b27286bfbc733629dd33dc575a2d1..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 103408 zcmce7bC7M#vS;J8ZQHiZ)9yZP+qP}nr~9;R+qP}n_Vo9@cW3U*yA${QF)=%0$BL@G zD)*}2FS9bUDi?{IuqX`!Eej+`*Hi8%Bm)CGK0UsTzBwc}H$I(|nYEFgy_vg_AwI)* z3!j0WiJ6`qpH2*41D}nF4WE&X0bdKBP8OemkrAIx1fPk8gNYuWP6nTW37<~!`*ud= z?=~+lq>;7ZUo!FkzkR+Z!tqZNQFOC4!lzS}H!}X7hLN?2qbWWsD?Xj5nWdwV{rA;U z&(TQO$iT+%`>wyQa(ebw4)}k8AY^0dWM%Du&x}teXK!R^X5eUJ|2^UFY2nkUd;`IN z&-nfQhC$rg(8%?#j&BSZSpV)Zw!vp&{(ca7d^&j>8^`Z)^nbS$zES;#>2IOVe?!Ia zf5Jm2E{w0i&0@$w&%(sWz+uEp&!n$!tjD0wz`@SJpr>cZ%EZdT&dbfj#KvyOs>i@) z$jHIWV5DzoOwVG>!ET_>z|5@2sL#Qx^%n^aj`l`+R*=4AMtO2Te z{Qd~UgRanGwxWO#i|(=KF!(*QQ2G@=5G~L71$7}}V-Z0RHOYJfGk|~rm`lM{{-X0g 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