R : Copyright 2005, The R Foundation for Statistical Computing
Version 2.1.1  (2005-06-20), ISBN 3-900051-07-0

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> ### * <HEADER>
> ###
> attach(NULL, name = "CheckExEnv")
> assign(".CheckExEnv", as.environment(2), pos = length(search())) # base
> ## add some hooks to label plot pages for base and grid graphics
> setHook("plot.new", ".newplot.hook")
> setHook("persp", ".newplot.hook")
> setHook("grid.newpage", ".gridplot.hook")
> 
> assign("cleanEx",
+        function(env = .GlobalEnv) {
+ 	   rm(list = ls(envir = env, all.names = TRUE), envir = env)
+            RNGkind("default", "default")
+ 	   set.seed(1)
+    	   options(warn = 1)
+ 	   delayedAssign("T", stop("T used instead of TRUE"),
+ 		  assign.env = .CheckExEnv)
+ 	   delayedAssign("F", stop("F used instead of FALSE"),
+ 		  assign.env = .CheckExEnv)
+ 	   sch <- search()
+ 	   newitems <- sch[! sch %in% .oldSearch]
+ 	   for(item in rev(newitems))
+                eval(substitute(detach(item), list(item=item)))
+ 	   missitems <- .oldSearch[! .oldSearch %in% sch]
+ 	   if(length(missitems))
+ 	       warning("items ", paste(missitems, collapse=", "),
+ 		       " have been removed from the search path")
+        },
+        env = .CheckExEnv)
> assign("..nameEx", "__{must remake R-ex/*.R}__", env = .CheckExEnv) # for now
> assign("ptime", proc.time(), env = .CheckExEnv)
> grDevices::postscript("bayesmix-Examples.ps")
> assign("par.postscript", graphics::par(no.readonly = TRUE), env = .CheckExEnv)
> options(contrasts = c(unordered = "contr.treatment", ordered = "contr.poly"))
> options(warn = 1)    
> library('bayesmix')
Loading required package: coda
> 
> assign(".oldSearch", search(), env = .CheckExEnv)
> assign(".oldNS", loadedNamespaces(), env = .CheckExEnv)
> cleanEx(); ..nameEx <- "BMMmodel"
> 
> ### * BMMmodel
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: BMMmodel
> ### Title: Creates text for .bug-file and data for -inits.R and
> ###   -data.R-file
> ### Aliases: BMMmodel print.JAGSmodel
> ### Keywords: utilities
> 
> ### ** Examples
> 
> data(fish)
> model <- BMMmodel(fish, k = 4, priors = list(kind = "independence",
+                   parameter = "priorsFish", hierarchical = "tau"),
+                   initialValues = list(S0 = 2))
> model
Data for nodes: b0, B0inv, nu0Half, g0Half, g0G0Half, k, N, e, y
Initial values for nodes: eta, mu, tau, S0

Model specification in BUGS language:

var 
	b0,
 	B0inv,
 	nu0Half,
 	g0Half,
 	g0G0Half,
 	k,
 	N,
 	eta[4], 
	mu[4], 
	tau[4], 
	S0,
 	nu0S0Half,
 	e[4], 
	y[256], 
	S[256]; 

model	{
	for (i in 1:N) {
		y[i] ~ dnorm(mu[S[i]],tau[S[i]]);
		S[i] ~ dcat(eta[]);
	}
	for (j in 1:k) {
		mu[j] ~ dnorm(b0,B0inv);
		tau[j] ~ dgamma(nu0Half,nu0S0Half);
	}
	S0 ~ dgamma(g0Half,g0G0Half);
	nu0S0Half <- nu0Half * S0;

	eta[] ~ ddirch(e[]);
}
> 
> 
> 
> cleanEx(); ..nameEx <- "BMMpriors"
> 
> ### * BMMpriors
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: BMMpriors
> ### Title: Creates a 'BMMpriors' object
> ### Aliases: BMMpriors
> ### Keywords: utilities
> 
> ### ** Examples
> 
>   data(fish)
>   priors <- BMMpriors(y = fish)
>   
> 
> 
> cleanEx(); ..nameEx <- "JAGScontrol"
> 
> ### * JAGScontrol
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: JAGScontrol
> ### Title: Creates text for .cmd file
> ### Aliases: JAGScontrol print.JAGScontrol
> ### Keywords: utilities
> 
> ### ** Examples
> 
> control <- JAGScontrol(variables = "mu")
> control
Commands for JAGS:

model in "jags.bug"
data in "jags-data.R"
compile
inits in "jags-inits.R"
initialize
monitor set mu
update 1000
coda *
exit
> 
> 
> 
> cleanEx(); ..nameEx <- "JAGSrun"
> 
> ### * JAGSrun
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: JAGSrun
> ### Title: MCMC sampling of Bayesian models
> ### Aliases: JAGSrun print.jags jags
> ### Keywords: utilities
> 
> ### ** Examples
> 
> data(fish)
> prefix <- "fish"
> variables <- c("mu","tau","eta")
> k <- 3
> modelFish <- BMMmodel(k = k, priors = list(kind = "independence",
+                       parameter = "priorsFish", hierarchical = "tau"))
> controlFish <- JAGScontrol(variables = c(variables, "S"), draw = 100, seed = 1)
> ## Installation of JAGS necessary for applying these functions
> if (haveJAGS()) {
+ z1 <- JAGSrun(fish, prefix, model = modelFish, initialValues = list(S0 = 2),
+               control = controlFish, cleanup = TRUE, tmp = FALSE)
+ zSort <- Sort(z1, "mu")
+ BMMposteriori(zSort)
+ }
> data(darwin)
> prefix <- "darwin"
> k <- 2
> modelDarwin <- BMMmodel(k = k, priors = list(kind = "independence",
+                         parameter = "priorsUncertain"), aprioriWeights = c(1, 15),
+                         no.empty.classes = TRUE, restrict = "tau")
> ## Installation of JAGS necessary for applying these functions
> if (haveJAGS()) {
+ z2 <- JAGSrun(darwin, prefix, model = modelDarwin, control =
+               JAGScontrol(variables = variables, draw = 3000, burnIn = 1000,
+               seed = 1), cleanup = TRUE, tmp = FALSE)
+ plot(z2, variables = "mu")
+ }
> 
> 
> 
> cleanEx(); ..nameEx <- "darwin"
> 
> ### * darwin
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: darwin
> ### Title: Differences in heights between plants
> ### Aliases: darwin
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(darwin)
> ## Estimated sample density
> plot(density(darwin[[1]]), ylim = c(0, 0.02), main = "Outlier modelling")
> ss <- seq(-100, 100, by = 1)
> ## Normal density with estimated mean and sd of whole sample
> lines(ss, dnorm(ss, mean = mean(darwin), sd = sd(darwin)), col = "red")
> ## Normal density with estimated mean and sd of sample, where the 2
> ## extremely small values are removed
> lines(ss, dnorm(ss, mean = mean(darwin[-c(1:2),1]), sd = sd(darwin[-c(1:2),1])),
+       col = "green")
> 
> 
> 
> cleanEx(); ..nameEx <- "fish"
> 
> ### * fish
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fish
> ### Title: Fish length data
> ### Aliases: fish
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(fish)
> ss <- seq(-3, 13, by = 0.01)
> hist(fish[[1]], 20, freq = FALSE, main = "Fish data")
> lines(ss, dnorm(ss, mean(fish), sd(fish)), col = "red")
> 
> 
> 
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", env = .CheckExEnv),"\n")
Time elapsed:  0.33 0.11 2.72 0.01 0.04 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')