[Depmix-commits] r257 - in trunk: . R man

[noreply at r-forge.r-project.org]

Author: ingmarvisser
Date: 2009-02-18 13:06:04 +0100 (Wed, 18 Feb 2009)
New Revision: 257

Modified:
   trunk/NEWS
   trunk/R/freepars.R
   trunk/man/responses.Rd
Log:
Changed order of examples in responses.Rd to match the order of models listed, and added some comments

Modified: trunk/NEWS
===================================================================
--- trunk/NEWS	2009-02-18 11:59:24 UTC (rev 256)
+++ trunk/NEWS	2009-02-18 12:06:04 UTC (rev 257)
@@ -1,23 +1,26 @@
 
 Changes in depmixS4 version 0.2-1
 
-  o Fixed a bug in the Viterbi algorithm used to compute posterior states
+  o fixed a bug in the Viterbi algorithm used to compute posterior states
   
-  o Restructured test files somewhat
+  o restructured test files somewhat
 
-  o Fixed a bug in the use of the conrows argument in the fit function (a missing
+  o fixed a bug in the use of the conrows argument in the fit function (a missing
     drop=FALSE statement)
 
-  o Updated help files for mix classes
+  o updated help files for mix classes
 
-  o Fixed a bug in setting the starting values of regression coefficients in 
+  o fixed a bug in setting the starting values of regression coefficients in 
     prior and transInit models with covariates (thanks to Verena Schmittmann 
     for reporting this)
 
-  o Added newx argument to predict function of transInit objects, to be used
+  o added newx argument to predict function of transInit objects, to be used
     for predicting probabilities depending on covariates (useful in eg plotting
     transition probabilities as function of a covariate)
 
+  o added example of the use of conrows argument in fitting functions and other 
+    minor updates in documentation
+  
   o 
 
 Changes in depmixS4 version 0.2-0

Modified: trunk/R/freepars.R
===================================================================
--- trunk/R/freepars.R	2009-02-18 11:59:24 UTC (rev 256)
+++ trunk/R/freepars.R	2009-02-18 12:06:04 UTC (rev 257)
@@ -27,7 +27,7 @@
 setMethod("nlin","mix.fitted",
 	function(object) {
 		conMat <- object at conMat[which(object at lin.lower==object at lin.upper),,drop=FALSE]
-		if(nrow(conMat==0) nlin <- 0 
+		if(nrow(conMat==0)) nlin <- 0 
 		else nlin <- qr(conMat)$rank
 		nlin
 	}
@@ -36,7 +36,7 @@
 setMethod("nlin","depmix.fitted",
 	function(object) {
 		conMat <- object at conMat[which(object at lin.lower==object at lin.upper),,drop=FALSE]
-		if(nrow(conMat==0) nlin <- 0 
+		if(nrow(conMat==0)) nlin <- 0 
 		else nlin <- qr(conMat)$rank
 		nlin
 	}
Modified: trunk/man/responses.Rd
===================================================================
--- trunk/man/responses.Rd	2009-02-18 11:59:24 UTC (rev 256)
+++ trunk/man/responses.Rd	2009-02-18 12:06:04 UTC (rev 257)
@@ -107,80 +107,57 @@
 
 \examples{
 	
-	mod <- GLMresponse(rnorm(1000)~1)
-
-	fit(mod)
-	
-	mod <- GLMresponse(sample(1:3,1000,rep=TRUE)~1,family=multinomial())
-	
-	fit(mod)
-	
-	colSums(mod at y)/1000
-	
-	x <- sample(0:1,1000,rep=TRUE)
-	
-	mod <- GLMresponse(sample(1:3,1000,rep=TRUE)~x,family=multinomial(),pstart=c(0.33,0.33,0.33,0,0,1))
-	
-	mod at y <- simulate(mod)
-	
-	fit(mod)
-	
-	colSums(mod at y[which(x==0),])/length(which(x==0))
-	
-	colSums(mod at y[which(x==1),])/length(which(x==1))
-
+	# binomial response model
 	x <- rnorm(1000)
-	
 	library(boot)
-	
 	p <- inv.logit(x)
-	
 	ss <- rbinom(1000,1,p)
-	
 	mod <- GLMresponse(cbind(ss,1-ss)~x,family=binomial())
-	
 	fit(mod)
-	
 	glm(cbind(ss,1-ss)~x, family=binomial)
 	
-	x <- abs(rnorm(1000,2))
-	
-	res <- rpois(1000,x)
-	
-	mod <- GLMresponse(res~x,family=poisson())
-	
-	fit(mod)
-	
-	glm(res~x, family=poisson)
-	
+	# gamma response model
 	x=runif(1000,1,5)
-	
 	res <- rgamma(1000,x)
-	
 	## note that gamma needs proper starting values which are not
 	## provided by depmixS4 (even with them, this may produce warnings)
 	mod <- GLMresponse(res~x,family=Gamma(),pst=c(0.8,1/0.8))
-	
 	fit(mod)
-	
 	glm(res~x,family=Gamma)
 	
-	mn <- c(1,2,3)
+	# multinomial response model
+	x <- sample(0:1,1000,rep=TRUE)
+	mod <- GLMresponse(sample(1:3,1000,rep=TRUE)~x,family=multinomial(),pstart=c(0.33,0.33,0.33,0,0,1))
+	mod at y <- simulate(mod)
+	fit(mod)
+	colSums(mod at y[which(x==0),])/length(which(x==0))
+	colSums(mod at y[which(x==1),])/length(which(x==1))
 	
+	# multivariate normal response model
+	mn <- c(1,2,3)
 	sig <- matrix(c(1,.5,0,.5,1,0,0,0,2),3,3)
-	
 	y <- mvrnorm(1000,mn,sig)
-	
 	mod <- MVNresponse(y~1)
-	
 	fit(mod)
-
 	colMeans(y)
-	
 	var(y)
 	
+	# normal (gaussian) response model
+	y <- rnorm(1000)
+	mod <- GLMresponse(y~1)
+	fm <- fit(mod)
+	cat("Test gaussian fit: ", all.equal(getpars(fm),c(mean(y),sd(y)),check=FALSE))
+	
+	
+	# poisson response model
+	x <- abs(rnorm(1000,2))
+	res <- rpois(1000,x)
+	mod <- GLMresponse(res~x,family=poisson())
+	fit(mod)
+	glm(res~x, family=poisson)
+	
 }
-
+	
 \author{Maarten Speekenbrink & Ingmar Visser}
 
 \keyword{models}