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("mixreg-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('mixreg')
> 
> assign(".oldSearch", search(), env = .CheckExEnv)
> assign(".oldNS", loadedNamespaces(), env = .CheckExEnv)
> cleanEx(); ..nameEx <- "bootcomp"
> 
> ### * bootcomp
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: bootcomp
> ### Title: Perform a bootstrap test for the number of components in a
> ###   mixture of regressions.
> ### Aliases: bootcomp
> ### Keywords: models regression
> 
> ### ** Examples
> 
> TS1 <- list(list(beta=c(3.0,0.1),sigsq=16,lambda=0.5),
+             list(beta=c(0.0,0.0),sigsq=16,lambda=0.5))
> TS2 <- list(list(beta=c(3.0,0.1),sigsq=9,lambda=1/3),
+             list(beta=c(1.5,0.05),sigsq=9,lambda=1/3),
+             list(beta=c(0.0,0.0),sigsq=9,lambda=1/3))
> data(aphids)
> x <- aphids$n.aphids
> y <- aphids$n.inf
> ## Not run: 
> ##D   nboot <- 1000
> ## End(Not run)
> ## Don't show:
>   nboot <- 10
> ## End Don't show
> boot.23 <- bootcomp(x,y,nboot=nboot,ts1=TS1,ts2=TS2)
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> 
> 
> 
> cleanEx(); ..nameEx <- "cband"
> 
> ### * cband
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: cband
> ### Title: Calculate confidence and prediction bands for mixtures of
> ###   one-variable regressions.
> ### Aliases: cband
> ### Keywords: models regression
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> cleanEx(); ..nameEx <- "covmix"
> 
> ### * covmix
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: covmix
> ### Title: Calculate the covariance matrix of the parameter estimates for a
> ###   mixture of regressions.
> ### Aliases: covmix
> ### Keywords: models regression
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> cleanEx(); ..nameEx <- "mixreg"
> 
> ### * mixreg
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: mixreg
> ### Title: Fit a mixture of linear regressions.
> ### Aliases: mixreg
> ### Keywords: models regression
> 
> ### ** Examples
> 
> data(aphids)
> x   <- aphids$n.aphids
> y   <- aphids$n.inf
> TS  <- list(list(beta=c(3.0,0.1),sigsq=16,lambda=0.5),
+             list(beta=c(0.0,0.0),sigsq=16,lambda=0.5))
> fit <- mixreg(x,y,ncomp=2,theta.start=TS,data.name='aphids')
     EM step 1:
     max abs. change in coef.: 6.401772
     EM step 2:
     max abs. change in coef.: 4.782379
     EM step 3:
     max abs. change in coef.: 1.928931
     EM step 4:
     max abs. change in coef.: 0.8011878
     EM step 5:
     max abs. change in coef.: 0.4412921
     EM step 6:
     max abs. change in coef.: 0.2338419
     EM step 7:
     max abs. change in coef.: 0.0984745
     EM step 8:
     max abs. change in coef.: 0.0351786
     EM step 9:
     max abs. change in coef.: 0.0192962
     EM step 10:
     max abs. change in coef.: 0.0115015
     EM step 11:
     max abs. change in coef.: 0.0058445
     EM step 12:
     max abs. change in coef.: 0.0027783
     EM step 13:
     max abs. change in coef.: 0.0012812
     EM step 14:
     max abs. change in coef.: 0.0005823
     EM step 15:
     max abs. change in coef.: 0.0002628
     EM step 16:
     max abs. change in coef.: 0.0001181
     EM step 17:
     max abs. change in coef.: 5.3e-05
     EM step 18:
     max abs. change in coef.: 2.37e-05
     EM step 19:
     max abs. change in coef.: 1.06e-05
     EM step 20:
     max abs. change in coef.: 4.8e-06
     EM step 21:
     max abs. change in coef.: 2.1e-06
     EM step 22:
     max abs. change in coef.: 1e-06
> cvm <- covmix(fit,x,y)
> cbd <- cband(fit,cvm,x,y)
> plot(cbd)
> r <- resid.mix(fit,x,y)
> plot(r)
> r <- resid.mix(fit,x,y,std=TRUE)
> qq.mix(r)
> 
> 
> 
> cleanEx(); ..nameEx <- "plot.cband"
> 
> ### * plot.cband
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot.cband
> ### Title: Plot confidence bands for a mixture of regressions.
> ### Aliases: plot.cband
> ### Keywords: models regression
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> cleanEx(); ..nameEx <- "plot.mresid"
> 
> ### * plot.mresid
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot.mresid
> ### Title: Plot residuals for a fitted mixture of linear regressions.
> ### Aliases: plot.mresid
> ### Keywords: models regression hplot
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> cleanEx(); ..nameEx <- "qq.mix"
> 
> ### * qq.mix
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: qq.mix
> ### Title: Draw a normal quantile-quantile plot of the residuals from a
> ###   fitted mixture of linear regressions.
> ### Aliases: qq.mix
> ### Keywords: models regression hplot
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> cleanEx(); ..nameEx <- "resid.mix"
> 
> ### * resid.mix
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: resid.mix
> ### Title: Calculate the residuals of a mixture of linear regressions.
> ### Aliases: resid.mix
> ### Keywords: models regression
> 
> ### ** Examples
> 
> #See mixreg for examples.
> 
> 
> 
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", env = .CheckExEnv),"\n")
Time elapsed:  28.23 0.07 28.48 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')