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("ismev-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('ismev')
> 
> assign(".oldSearch", search(), env = .CheckExEnv)
> assign(".oldNS", loadedNamespaces(), env = .CheckExEnv)
> cleanEx(); ..nameEx <- "gev.diag"
> 
> ### * gev.diag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gev.diag
> ### Title: Diagnostic Plots for GEV Models
> ### Aliases: gev.diag
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(portpirie)
> ppfit <- gev.fit(portpirie[,2])
$conv
[1] 0

$nllh
[1] -4.339058

$mle
[1]  3.87474692  0.19804120 -0.05008773

$se
[1] 0.02793211 0.02024610 0.09825633

> gev.diag(ppfit)
> 
> 
> 
> cleanEx(); ..nameEx <- "gev.fit"
> 
> ### * gev.fit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gev.fit
> ### Title: Maximum-likelihood Fitting of the GEV Distribution
> ### Aliases: gev.fit
> ### Keywords: models
> 
> ### ** Examples
> 
> data(portpirie)
> gev.fit(portpirie[,2])
$conv
[1] 0

$nllh
[1] -4.339058

$mle
[1]  3.87474692  0.19804120 -0.05008773

$se
[1] 0.02793211 0.02024610 0.09825633

> 
> 
> 
> cleanEx(); ..nameEx <- "gev.prof"
> 
> ### * gev.prof
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gev.prof
> ### Title: Profile Log-likelihoods for Stationary GEV Models
> ### Aliases: gev.prof gev.profxi
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(portpirie)
> ppfit <- gev.fit(portpirie[,2])
$conv
[1] 0

$nllh
[1] -4.339058

$mle
[1]  3.87474692  0.19804120 -0.05008773

$se
[1] 0.02793211 0.02024610 0.09825633

> ## Not run: gev.prof(ppfit, m = 10, 4.1, 5)
> ## Not run: gev.profxi(ppfit, -0.3, 0.3)
> 
> 
> 
> cleanEx(); ..nameEx <- "gpd.diag"
> 
> ### * gpd.diag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gpd.diag
> ### Title: Diagnostic Plots for GPD Models
> ### Aliases: gpd.diag
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(rain)
> rnfit <- gpd.fit(rain, 10)
$threshold
[1] 10

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 6123.465

$mle
[1] 7.43736339 0.05049163

$rate
[1] 0.1142547

$se
[1] 0.23606332 0.02256987

> gpd.diag(rnfit)
> 
> 
> 
> cleanEx(); ..nameEx <- "gpd.fit"
> 
> ### * gpd.fit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gpd.fit
> ### Title: Maximum-likelihood Fitting for the GPD Model
> ### Aliases: gpd.fit
> ### Keywords: models
> 
> ### ** Examples
> 
> data(rain)
> gpd.fit(rain, 10)
$threshold
[1] 10

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 6123.465

$mle
[1] 7.43736339 0.05049163

$rate
[1] 0.1142547

$se
[1] 0.23606332 0.02256987

> 
> 
> 
> cleanEx(); ..nameEx <- "gpd.fitrange"
> 
> ### * gpd.fitrange
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gpd.fitrange
> ### Title: Fitting the GPD Model Over a Range of Thresholds
> ### Aliases: gpd.fitrange
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## Not run: data(rain)
> ## Not run: gpd.fitrange(rain, 10, 40)
> 
> 
> 
> cleanEx(); ..nameEx <- "gpd.prof"
> 
> ### * gpd.prof
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gpd.prof
> ### Title: Profile Log-likelihoods for Stationary GPD Models
> ### Aliases: gpd.prof gpd.profxi
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(rain)
> rnfit <- gpd.fit(rain, 10)
$threshold
[1] 10

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 6123.465

$mle
[1] 7.43736339 0.05049163

$rate
[1] 0.1142547

$se
[1] 0.23606332 0.02256987

> ## Not run: gpd.prof(rnfit, m = 10, 55, 75)
> ## Not run: gpd.profxi(rnfit, -0.02, 0.15)
> 
> 
> 
> cleanEx(); ..nameEx <- "gum.diag"
> 
> ### * gum.diag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gum.diag
> ### Title: Diagnostic Plots for Gumbel Models
> ### Aliases: gum.diag
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(portpirie)
> ppfit <- gum.fit(portpirie[,2])
$conv
[1] 0

$nllh
[1] -4.217682

$mle
[1] 3.8694426 0.1948867

$se
[1] 0.02549356 0.01885190

> gum.diag(ppfit)
> 
> 
> 
> cleanEx(); ..nameEx <- "gum.fit"
> 
> ### * gum.fit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gum.fit
> ### Title: Maximum-likelihood Fitting of the Gumbel Distribution
> ### Aliases: gum.fit
> ### Keywords: models
> 
> ### ** Examples
> 
> data(portpirie)
> gum.fit(portpirie[,2])
$conv
[1] 0

$nllh
[1] -4.217682

$mle
[1] 3.8694426 0.1948867

$se
[1] 0.02549356 0.01885190

> 
> 
> 
> cleanEx(); ..nameEx <- "mrl.plot"
> 
> ### * mrl.plot
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: mrl.plot
> ### Title: Mean Residual Life Plot
> ### Aliases: mrl.plot
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(rain)
> mrl.plot(rain)
> 
> 
> 
> cleanEx(); ..nameEx <- "pp.diag"
> 
> ### * pp.diag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pp.diag
> ### Title: Diagnostic Plots for Point Process Models
> ### Aliases: pp.diag
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(rain)
> rnfit <- pp.fit(rain, 10)
$threshold
[1] 10

$npy
[1] 365

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 654.1278

$mle
[1] 40.52563862  8.97657314  0.05044411

$se
[1] 0.99990549 0.60010762 0.02251094

> pp.diag(rnfit)
> 
> 
> 
> cleanEx(); ..nameEx <- "pp.fit"
> 
> ### * pp.fit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pp.fit
> ### Title: Maximum-likelihood Fitting for the Point Process Model
> ### Aliases: pp.fit
> ### Keywords: models
> 
> ### ** Examples
> 
> data(rain)
> pp.fit(rain, 10)
$threshold
[1] 10

$npy
[1] 365

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 654.1278

$mle
[1] 40.52563862  8.97657314  0.05044411

$se
[1] 0.99990549 0.60010762 0.02251094

> 
> 
> 
> cleanEx(); ..nameEx <- "pp.fitrange"
> 
> ### * pp.fitrange
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pp.fitrange
> ### Title: Fitting the Point Process Model Over a Range of Thresholds
> ### Aliases: pp.fitrange
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## Not run: data(rain)
> ## Not run: pp.fitrange(rain, 10, 40)
> 
> 
> 
> cleanEx(); ..nameEx <- "rlarg.diag"
> 
> ### * rlarg.diag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: rlarg.diag
> ### Title: Diagnostic Plots for Order Statistics Models
> ### Aliases: rlarg.diag
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## Not run: data(venice)
> ## Not run: venfit <- rlarg.fit(venice[,-1])
> ## Not run: rlarg.diag(venfit)
> 
> 
> 
> cleanEx(); ..nameEx <- "rlarg.fit"
> 
> ### * rlarg.fit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: rlarg.fit
> ### Title: Maximum-likelihood Fitting of Order Statistics Model
> ### Aliases: rlarg.fit
> ### Keywords: models
> 
> ### ** Examples
> 
> ## Not run: data(venice)
> ## Not run: rlarg.fit(venice[,-1])
> 
> 
> 
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", env = .CheckExEnv),"\n")
Time elapsed:  5.19 2.03 7.26 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')