[Distr-commits] r715 - pkg/distrEx/tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri Jan 7 10:23:40 CET 2011
Author: stamats
Date: 2011-01-07 10:23:40 +0100 (Fri, 07 Jan 2011)
New Revision: 715
Modified:
pkg/distrEx/tests/Examples/distrEx-Ex.Rout.save
Log:
updated distrEx-Ex.Rout.save files to R 2.12.1 patched
Modified: pkg/distrEx/tests/Examples/distrEx-Ex.Rout.save
===================================================================
--- pkg/distrEx/tests/Examples/distrEx-Ex.Rout.save 2011-01-06 23:34:26 UTC (rev 714)
+++ pkg/distrEx/tests/Examples/distrEx-Ex.Rout.save 2011-01-07 09:23:40 UTC (rev 715)
@@ -1,7 +1,8 @@
-R version 2.10.1 Patched (2010-01-12 r50990)
-Copyright (C) 2010 The R Foundation for Statistical Computing
+R version 2.12.1 Patched (2011-01-04 r53913)
+Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
+Platform: x86_64-unknown-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
@@ -31,8 +32,7 @@
Loading required package: sfsmisc
Loading required package: SweaveListingUtils
:SweaveListingUtils> Utilities for Sweave together with
-:SweaveListingUtils> TeX listings package (version
-:SweaveListingUtils> 0.4.1)
+:SweaveListingUtils> TeX listings package (version 0.5)
:SweaveListingUtils>
:SweaveListingUtils> Some functions from package 'base'
:SweaveListingUtils> are intentionally masked ---see
@@ -53,14 +53,12 @@
Attaching package: 'SweaveListingUtils'
+The following object(s) are masked from 'package:base':
- The following object(s) are masked from package:base :
+ library, require
- library,
- require
-
-:distr> Object orientated implementation of distributions (version
-:distr> 2.2.1)
+:distr> Object oriented implementation of distributions (version
+:distr> 2.3)
:distr>
:distr> Attention: Arithmetics on distribution objects are
:distr> understood as operations on corresponding random variables
@@ -81,24 +79,20 @@
Attaching package: 'distr'
+The following object(s) are masked from 'package:stats':
- The following object(s) are masked from package:stats :
+ df, qqplot, sd
- df,
- qqplot,
- sd
-
Loading required package: evd
Loading required package: actuar
Attaching package: 'actuar'
+The following object(s) are masked from 'package:grDevices':
- The following object(s) are masked from package:grDevices :
+ cm
- cm
-
-:distrEx> Extensions of package distr (version 2.2.1)
+:distrEx> Extensions of package distr (version 2.3)
:distrEx>
:distrEx> Note: Packages "e1071", "moments", "fBasics" should be
:distrEx> attached /before/ package "distrEx". See distrExMASK().
@@ -113,14 +107,10 @@
Attaching package: 'distrEx'
+The following object(s) are masked from 'package:stats':
- The following object(s) are masked from package:stats :
+ IQR, mad, median, var
- IQR,
- mad,
- median,
- var
-
>
> assign(".oldSearch", search(), pos = 'CheckExEnv')
> cleanEx()
@@ -175,7 +165,7 @@
0.2316870
> AsymTotalVarDist(Norm(), Td(10), rho=0.3)
asym. total variation distance
- 0.03412602
+ 0.03412603
> AsymTotalVarDist(Norm(mean = 50, sd = sqrt(25)), Binom(size = 100), rho=0.3) # mutually singular
asym. total variation distance
1
@@ -197,7 +187,7 @@
0.8343428
> AsymTotalVarDist(y, Norm(), asis.smooth.discretize = "smooth", rho=0.3)
asym. total variation distance
- 0.6326863
+ 0.6326877
>
> AsymTotalVarDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5), rho=0.3)
asym. total variation distance
@@ -333,13 +323,13 @@
0.06084579
> CvMDist(rnorm(100),Norm())
CvM distance
- 0.04673208
+ 0.04673118
> CvMDist((rbinom(50, size = 20, prob = 0.5)-10)/sqrt(5), Norm())
CvM distance
- 0.07266983
+ 0.07267501
> CvMDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5))
CvM distance
- 0.1205683
+ 0.07435729
> CvMDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5), mu = Pois())
CvM distance
0.001969063
@@ -524,7 +514,8 @@
> ### E,Fd,missing,missing-method E,Gammad,missing,missing-method
> ### E,Gammad,function,missing-method E,Geom,missing,missing-method
> ### E,Gumbel,missing,missing-method E,GPareto,missing,missing-method
-> ### E,GPareto,function,missing-method E,Hyper,missing,missing-method
+> ### E,GPareto,function,missing-method E,GEV,missing,missing-method
+> ### E,GEV,function,missing-method E,Hyper,missing,missing-method
> ### E,Logis,missing,missing-method E,Lnorm,missing,missing-method
> ### E,Nbinom,missing,missing-method E,Norm,missing,missing-method
> ### E,Pareto,missing,missing-method E,Pois,missing,missing-method
@@ -660,6 +651,100 @@
>
>
> cleanEx()
+> nameEx("GEV-class")
+> ### * GEV-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: GEV-class
+> ### Title: Generalized EV distribution
+> ### Aliases: GEV-class initialize,GEV-method loc,GEV-method
+> ### loc<-,GEV-method location,GEV-method location<-,GEV-method
+> ### scale,GEV-method scale<-,GEV-method shape,GEV-method
+> ### shape<-,GEV-method +,GEV,numeric-method *,GEV,numeric-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> (P1 <- new("GEV", loc = 0, scale = 1,shape = 0))
+Distribution Object of Class: GEV
+ loc: 0
+ scale: 1
+ shape: 0
+> plot(P1)
+> shape(P1)
+[1] 0
+> loc(P1)
+[1] 0
+> scale(P1) <- 4
+> loc(P1) <- 2
+> plot(P1)
+>
+>
+>
+> cleanEx()
+> nameEx("GEV")
+> ### * GEV
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: GEV
+> ### Title: Generating function for GEV-class
+> ### Aliases: GEV
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> (P1 <- GEV(loc = 0, scale = 1, shape = 0))
+Distribution Object of Class: GEV
+ loc: 0
+ scale: 1
+ shape: 0
+> plot(P1)
+>
+> E(GEV())
+[1] 0.5772157
+> E(P1, function(x){x^2})
+[1] 1.977920
+>
+>
+>
+>
+> cleanEx()
+> nameEx("GEVParameter-class")
+> ### * GEVParameter-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: GEVParameter-class
+> ### Title: Parameter of generalized Pareto distributions
+> ### Aliases: GEVParameter-class loc,GEVParameter-method
+> ### loc<-,GEVParameter-method location,GEVParameter-method
+> ### location<-,GEVParameter-method scale,GEVParameter-method
+> ### scale<-,GEVParameter-method shape,GEVParameter-method
+> ### shape<-,GEVParameter-method
+> ### Keywords: distribution models
+>
+> ### ** Examples
+>
+> new("GEVParameter")
+An object of class "GEVParameter"
+Slot "loc":
+[1] 0
+
+Slot "scale":
+[1] 1
+
+Slot "shape":
+[1] 0.5
+
+Slot "name":
+[1] "Parameter of a generalized extreme value distribution"
+
+>
+>
+>
+> cleanEx()
> nameEx("GLIntegrate")
> ### * GLIntegrate
>
@@ -918,7 +1003,7 @@
0.3287617
> HellingerDist(x, Norm(), asis.smooth.discretize = "smooth")
Hellinger distance
- 0.1904838
+ 0.1904784
>
> y <- (rbinom(50, size = 20, prob = 0.5)-10)/sqrt(5)
> HellingerDist(y, Norm())
@@ -926,7 +1011,7 @@
0.7596996
> HellingerDist(y, Norm(), asis.smooth.discretize = "smooth")
Hellinger distance
- 0.5283272
+ 0.528329
>
> HellingerDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5))
Hellinger distance
@@ -1019,7 +1104,7 @@
}
0 + cond %*% 1 + 1 * r(n, ...)
}
-<environment: 0x66e5258>
+<environment: 0x36087e8>
> d(D1)
function (x, cond, log = FALSE, ...)
{
@@ -1041,7 +1126,7 @@
else d0 <- d0/1
return(d0)
}
-<environment: 0x66e5258>
+<environment: 0x36087e8>
> p(D1)
function (q, cond, lower.tail = TRUE, log.p = FALSE, ...)
{
@@ -1068,7 +1153,7 @@
p0 <- log(p0)
return(p0)
}
-<environment: 0x66e5258>
+<environment: 0x36087e8>
> q(D1)
function (p, cond, lower.tail = TRUE, log.p = FALSE, ...)
{
@@ -1092,7 +1177,7 @@
argList <- c(argList, dots)
1 * do.call(q, argList) + 0 + as.vector(cond %*% 1)
}
-<environment: 0x66e5258>
+<environment: 0x36087e8>
> param(D1)
name: parameter of a linear regression model
theta: 1
@@ -1234,7 +1319,7 @@
0.8150567
> OAsymTotalVarDist(x, Norm(), asis.smooth.discretize = "smooth")
minimal asym. total variation distance
- 0.345616
+ 0.3454698
>
> y <- (rbinom(50, size = 20, prob = 0.5)-10)/sqrt(5)
> OAsymTotalVarDist(y, Norm())
@@ -1242,7 +1327,7 @@
0.9201529
> OAsymTotalVarDist(y, Norm(), asis.smooth.discretize = "smooth")
minimal asym. total variation distance
- 0.7539696
+ 0.753965
>
> OAsymTotalVarDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5))
minimal asym. total variation distance
@@ -1428,7 +1513,7 @@
0.1501365
> TotalVarDist(Norm(), Td(10))
total variation distance
- 0.0310744
+ 0.03107182
> TotalVarDist(Norm(mean = 50, sd = sqrt(25)), Binom(size = 100)) # mutually singular
total variation distance
1
@@ -1498,10 +1583,10 @@
> ### var,Arcsine-method var,Beta-method var,Binom-method var,Cauchy-method
> ### var,Chisq-method var,Dirac-method var,DExp-method var,Exp-method
> ### var,Fd-method var,Gammad-method var,Geom-method var,Gumbel-method
-> ### var,GPareto-method var,Hyper-method var,Logis-method var,Lnorm-method
-> ### var,Nbinom-method var,Norm-method var,Pareto-method var,Pois-method
-> ### var,Unif-method var,Weibull-method var,Td-method sd sd-methods
-> ### sd,UnivariateDistribution-method sd,Norm-method median
+> ### var,GPareto-method var,GEV-method var,Hyper-method var,Logis-method
+> ### var,Lnorm-method var,Nbinom-method var,Norm-method var,Pareto-method
+> ### var,Pois-method var,Unif-method var,Weibull-method var,Td-method sd
+> ### sd-methods sd,UnivariateDistribution-method sd,Norm-method median
> ### median,ANY-method median-methods median,UnivariateDistribution-method
> ### median,UnivariateCondDistribution-method
> ### median,AffLinDistribution-method
@@ -1510,18 +1595,20 @@
> ### median,AffLinLatticeDistribution-method median,Arcsine-method
> ### median,Cauchy-method median,Dirac-method median,DExp-method
> ### median,Exp-method median,Geom-method median,Gumbel-method
-> ### median,GPareto-method median,Logis-method median,Lnorm-method
-> ### median,Norm-method median,Pareto-method median,Unif-method IQR
-> ### IQR-methods IQR,ANY-method IQR,UnivariateDistribution-method
+> ### median,GEV-method median,GPareto-method median,Logis-method
+> ### median,Lnorm-method median,Norm-method median,Pareto-method
+> ### median,Unif-method IQR IQR-methods IQR,ANY-method
+> ### IQR,UnivariateDistribution-method
> ### IQR,UnivariateCondDistribution-method IQR,AffLinDistribution-method
> ### IQR,AffLinAbscontDistribution-method
> ### IQR,AffLinDiscreteDistribution-method
> ### IQR,AffLinLatticeDistribution-method IQR,DiscreteDistribution-method
> ### IQR,Arcsine-method IQR,Cauchy-method IQR,Dirac-method IQR,DExp-method
> ### IQR,Exp-method IQR,Geom-method IQR,Gumbel-method IQR,GPareto-method
-> ### IQR,Logis-method IQR,Norm-method IQR,Pareto-method IQR,Unif-method
-> ### mad mad,ANY-method mad-methods mad,UnivariateDistribution-method
-> ### mad,AffLinDistribution-method mad,AffLinAbscontDistribution-method
+> ### IQR,GEV-method IQR,Logis-method IQR,Norm-method IQR,Pareto-method
+> ### IQR,Unif-method mad mad,ANY-method mad-methods
+> ### mad,UnivariateDistribution-method mad,AffLinDistribution-method
+> ### mad,AffLinAbscontDistribution-method
> ### mad,AffLinDiscreteDistribution-method
> ### mad,AffLinLatticeDistribution-method mad,Cauchy-method
> ### mad,Dirac-method mad,DExp-method mad,Exp-method mad,Geom-method
@@ -1535,12 +1622,12 @@
> ### skewness,Beta-method skewness,Binom-method skewness,Cauchy-method
> ### skewness,Chisq-method skewness,Dirac-method skewness,DExp-method
> ### skewness,Exp-method skewness,Fd-method skewness,Gammad-method
-> ### skewness,Geom-method skewness,Gumbel-method skewness,GPareto-method
-> ### skewness,Hyper-method skewness,Logis-method skewness,Lnorm-method
-> ### skewness,Nbinom-method skewness,Norm-method skewness,Pareto-method
-> ### skewness,Pois-method skewness,Unif-method skewness,Weibull-method
-> ### skewness,Td-method kurtosis kurtosis-methods kurtosis,ANY-method
-> ### kurtosis,UnivariateDistribution-method
+> ### skewness,Geom-method skewness,Gumbel-method skewness,GEV-method
+> ### skewness,GPareto-method skewness,Hyper-method skewness,Logis-method
+> ### skewness,Lnorm-method skewness,Nbinom-method skewness,Norm-method
+> ### skewness,Pareto-method skewness,Pois-method skewness,Unif-method
+> ### skewness,Weibull-method skewness,Td-method kurtosis kurtosis-methods
+> ### kurtosis,ANY-method kurtosis,UnivariateDistribution-method
> ### kurtosis,AffLinDistribution-method
> ### kurtosis,AffLinAbscontDistribution-method
> ### kurtosis,AffLinDiscreteDistribution-method
@@ -1548,11 +1635,11 @@
> ### kurtosis,Beta-method kurtosis,Binom-method kurtosis,Cauchy-method
> ### kurtosis,Chisq-method kurtosis,Dirac-method kurtosis,DExp-method
> ### kurtosis,Exp-method kurtosis,Fd-method kurtosis,Gammad-method
-> ### kurtosis,Geom-method kurtosis,Gumbel-method kurtosis,GPareto-method
-> ### kurtosis,Hyper-method kurtosis,Logis-method kurtosis,Lnorm-method
-> ### kurtosis,Nbinom-method kurtosis,Norm-method kurtosis,Pareto-method
-> ### kurtosis,Pois-method kurtosis,Unif-method kurtosis,Weibull-method
-> ### kurtosis,Td-method
+> ### kurtosis,Geom-method kurtosis,Gumbel-method kurtosis,GEV-method
+> ### kurtosis,GPareto-method kurtosis,Hyper-method kurtosis,Logis-method
+> ### kurtosis,Lnorm-method kurtosis,Nbinom-method kurtosis,Norm-method
+> ### kurtosis,Pareto-method kurtosis,Pois-method kurtosis,Unif-method
+> ### kurtosis,Weibull-method kurtosis,Td-method
> ### Keywords: methods distribution
>
> ### ** Examples
@@ -1584,7 +1671,7 @@
[1] 8.485224
> #
> mad(sin(exp(Norm()+2*Pois()))) ## weird
-[1] 0.5085796
+[1] 0.499821
>
>
>
@@ -1700,7 +1787,7 @@
> flush(stderr()); flush(stdout())
>
> ### Name: distrExOptions
-> ### Title: Function to change the global variables of the package `distrEx'
+> ### Title: Function to change the global variables of the package 'distrEx'
> ### Aliases: distrExOptions distrExoptions getdistrExOption MCIterations
> ### GLIntegrateTruncQuantile GLIntegrateOrder ElowerTruncQuantile
> ### EupperTruncQuantile ErelativeTolerance m1dfLowerTruncQuantile
@@ -1763,6 +1850,29 @@
>
>
> cleanEx()
+> nameEx("kMAD")
+> ### * kMAD
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: kMAD
+> ### Title: Asymmetric Median of Absolute Deviations for Skewed
+> ### Distributions
+> ### Aliases: kMAD kMAD-methods kMAD,UnivariateDistribution,numeric-method
+> ### kMAD,numeric,numeric-method
+> ### Keywords: scale estimator
+>
+> ### ** Examples
+>
+> x <- rnorm(100)
+> kMAD(x,k=10)
+[1] 0.1351646
+> kMAD(Norm(),k=10)
+[1] 0.1543645
+>
+>
+>
+> cleanEx()
> nameEx("liesInSupport")
> ### * liesInSupport
>
@@ -1893,7 +2003,7 @@
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed: 14.91 0.22 15.161 0.01 0.01
+Time elapsed: 14.23 0.12 14.519 0 0
> grDevices::dev.off()
null device
1
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