Running examples in ‘StagedChoiceSplineMix-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: StagedChoiceSplineMix
> ### Title: Performs iterations between an EM algorithm for a mixture of
> ###   two-stage logistic regressions with fixed candidate knots and knot
> ###   movements
> ### Aliases: StagedChoiceSplineMix
> 
> ### ** Examples
> 
> #######################################
> ###### 1. Generate data (simdata) #####
> set.seed(77)
> k<-3
> 
> betab<-matrix(c(1.5,2.0,0.3,-0.2,-0.1,0.6,-2.5,0.5,1,3,-1,1,2,-0.5,-1.5),5,k,byrow=TRUE)
> betaw<-matrix(c(-2.0,-1,0.3,-0.3,-0.2,0.2,-3,-2,0,3,2,-1.5,3,2,-1),5,k,byrow=TRUE)
> sp1.knots<-matrix(c(8,14,4,11,5,15,5,12,5,13,7,14),3,4,byrow=TRUE)
> lambda<-c(0.3,0.3,0.4)
> 
> # Large data set
> #n_id<-700
> #nobsb<-200
> 
> # Small data set
> n_id<-100
> nobsb<-100
> 
> nb<-n_id*nobsb
> 
> idb <- rep(1:n_id, each=nobsb)
> 
> xb.1<-rbinom(nb,size=1,prob=0.7)
> xb.com<-cbind(1,xb.1)
> xb.sp1<-runif((nb),-2,2)
> xb<-cbind(xb.com,xb.sp1)
> 
> sp1.mat.b<- matrix(double(20*nb),ncol=20)
> sp1.mat.b[,1]<-xb.sp1
> sp1.quan<-quantile(xb.sp1,c(0.05,0.1,0.15,0.2,0.25,0.3,0.35,0.4,0.45,0.5,
+ 0.55,0.6,0.65,0.7,0.75,0.8,0.85,0.9,0.95))
> 
> for (i in 1:19){
+    sp1.mat.b[,(i+1)]<-xb.sp1-sp1.quan[i]
+ }
> sp1.mat.b[sp1.mat.b<0]<-0
> sp1.mat.b[,1]<-xb.sp1
> 
> xb.class<-list()
> for (i in 1:k){
+   xb.class[[i]]<-cbind(xb.com,sp1.mat.b[,1],sp1.mat.b[,(sp1.knots[i,1:2])+1])
+ }
> 
> xbetab<-matrix(double(nb*k),ncol=k)
> for (i in 1:k){
+   xbetab[,i]<-data.matrix(xb.class[[i]])%*%betab[,i]
+ }
> 
> num.idb<-as.vector(ddply(data.frame(idb),"idb",count)[,-1])
> 
> w<-sample(c(1:k), n_id, replace = TRUE, prob = lambda)
> wb<-rep(w,num.idb)
> yb.temp<-matrix(double(nb*k),ncol=k)
> 
> for (i in 1:k){
+   yb.temp[,i]<-rbinom((nb), size = 1, prob = (1/(1+exp(-xbetab[, i]))))
+ }
> yb<-sapply(1:nb, function(i) yb.temp[i,wb[i]])
> 
> idw<-idb[yb==1]
> nw<-length(idw)
> sp1.mat.w<-sp1.mat.b[yb==1,]
> xw.com<-xb.com[yb==1,]
> xw<-xb[yb==1,]
> 
> xw.class<-list()
> for (i in 1:k){
+   xw.class[[i]]<-cbind(xw.com,sp1.mat.w[,1],sp1.mat.w[,(sp1.knots[i,3:4])+1])
+ }
> 
> xbetaw<-matrix(double(nw*k),ncol=k)
> for (i in 1:k){
+   xbetaw[,i]<-data.matrix(xw.class[[i]])%*%betaw[,i]
+ }
> 
> num.idw<-as.vector(ddply(data.frame(idw),"idw",count)[,-1])
> ww<-wb[yb==1]
> 
> yw.temp<-matrix(double(nw*k),ncol=k)
> for (i in 1:k){
+   yw.temp[,i]<-rbinom((nw), size = 1, prob = (1/(1+exp(-xbetaw[, i]))))
+ }
> yw<-sapply(1:nw, function(i) yw.temp[i,ww[i]])
> 
> yb.aug<-cbind(1:length(yb),yb)
> yw.aug<-cbind(which(yb==1),yw)
> 
> colnames(yb.aug)[1]<-"num"
> colnames(yw.aug)[1]<-"num"
> 
> ybyw<-merge(yb.aug,yw.aug, all = TRUE)[,-1]
> 
> simdata<-cbind(idb,ybyw,xb.1,sp1.mat.b[,1])
> simdata[is.na(simdata)]<-""
> simdata[,3]<-as.integer(simdata[,3])
> colnames(simdata)[1]<-"userid"
> colnames(simdata)[2]<-"browsed"
> colnames(simdata)[3]<-"wrote"
> colnames(simdata)[4]<-"x1"
> colnames(simdata)[5]<-"sp1"
> 
> ########################################
> ##### 2. Run StagedChoiceSplineMix #####
> ## number of latent classes
> set.seed(66)
> k<-3
> 
> ## starting points: true parameters used in the data generation (optional)
> betab<-matrix(c(1.5,2.0,0.3,-0.2,-0.1,0.6,-2.5,0.5,1,3,-1,1,2,-0.5,-1.5),5,k,byrow=TRUE)
> betaw<-matrix(c(-2.0,-1,0.3,-0.3,-0.2,0.2,-3,-2,0,3,2,-1.5,3,2,-1),5,k,byrow=TRUE)
> lambda<-c(0.3,0.3,0.4)
> 
> ## number of random multiple starting points to try given a knot configuration
> nst<-1
> 
> ## vector of the columns of spline variables in the data set (required)
> sp.cols<-5
> 
> # vector of the numbers of candidate knots for splined variables (optional)
> num.knots<-19
> 
> ## true knot configuration used in the data generation
> sp1.knots<-matrix(c(8,14,4,11,5,15,5,12,5,13,7,14),3,4,byrow=TRUE)
> 
> ## list of knot configuration of spline variables (optional)
> sp.knots<-list(sp1.knots)
> 
> ## Run "StagedChoiceSplineMix"
> out<-StagedChoiceSplineMix(data=simdata, M=1, sp.cols=sp.cols, num.knots, sp.knots,
+ betab, betaw, lambda, k=k, nst=nst, epsilon=1e-06, maxit=500, maxrestarts=100, maxer=20)

************************************************************* 
*** Knot configuration:  1 
************************************************************* 
Number of errors within a knot configuration:  0 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  1 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  2 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  3 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  4 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  5 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  6 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  7 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  8 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  9 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  10 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  11 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  12 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  13 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  14 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  15 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  16 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  17 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  18 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Number of errors within a knot configuration:  19 
Error in Summary.factor(structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  : 
  ‘max’ not meaningful for factors
Error in if (ll.old <= bestst$loglik) { : argument is of length zero
Calls: StagedChoiceSplineMix
Execution halted