| Title: | Distribution Classes for Distributions from Rmetrics |
|---|---|
| Description: | S4-distribution classes based on package distr for distributions from packages 'fBasics' and 'fGarch'. |
| Authors: | Peter Ruckdeschel [cre, cph, aut] |
| Maintainer: | Peter Ruckdeschel <[email protected]> |
| License: | LGPL-3 |
| Version: | 2.8.2 |
| Built: | 2024-11-06 02:16:29 UTC |
| Source: | https://github.com/r-forge/distr |
distrRmetrics provides infrastructure / (S4-)classes (based on package distr) for distributions contributed in the Rmetrics packages.
| Package: | distrRmetrics |
| Version: | 2.8.2 |
| Date: | 2024-01-30 |
| Depends: | R(>= 3.4), methods, distr(>= 2.4), fBasics(>= 270.73), fGarch(>= 270.73) |
| Suggests: | distrEx(>= 2.4), distrMod(>= 2.4) |
| Imports: startupmsg | |
| ByteCompile: | yes |
| License: | LGPL-3 |
| URL: | https://distr.r-forge.r-project.org/ |
| VCS/SVNRevision: | 1427 |
################################### Distribution Classes ################################### [*]: there is a generating function with the same name "Distribution" (from distr) |>"AbscontDistribution" (from distr) |>|>"SNorm" [*] |>|>"SSTd" [*]
STd Functions to generate an "AbscontDistribution" object implementing
a standardized T distribution
All slots are inspected / modified by corresponding accessors / -replacement functions.
You may suppress the start-up banner/message completely by setting options("StartupBanner"="off")
somewhere before loading this package by library or require in your R-code / R-session.
If option "StartupBanner" is not defined (default) or setting
options("StartupBanner"=NULL) or options("StartupBanner"="complete")
the complete start-up banner is displayed.
For any other value of option "StartupBanner" (i.e., not in c(NULL,"off","complete"))
only the version information is displayed.
The same can be achieved by wrapping the library or require call into
either suppressStartupMessages() or
onlytypeStartupMessages(.,atypes="version").
As for general packageStartupMessage's, you may also suppress all
the start-up banner by wrapping the library or require
call into suppressPackageStartupMessages() from
startupmsg-version 0.5 on.
Note: The first two numbers of package versions do not necessarily reflect package-individual development, but rather are chosen for the distrXXX family as a whole in order to ease updating "depends" information.
Peter Ruckdeschel [email protected],
Maintainer: Peter Ruckdeschel [email protected]
P. Ruckdeschel, M. Kohl, T. Stabla, F. Camphausen (2006):
S4 Classes for Distributions, R News, 6(2), 2-6.
https://CRAN.R-project.org/doc/Rnews/Rnews_2006-2.pdf
A vignette for packages distr, distrSim, distrTEst, distrEx,
distrTeach, distrMod, and distrRmetrics
is included into the mere documentation package distrDoc and may be called by
require("distrDoc");vignette("distr").
A homepage to this package is available under
https://distr.r-forge.r-project.org/.
Generates an object of class "SNorm".
SNorm(mean = 0, sd = 1, xi = 1.5)SNorm(mean = 0, sd = 1, xi = 1.5)
mean |
real number: location parameter of the SNorm distribution. |
sd |
positive real number: scale parameter of the SNorm distribution |
xi |
positive real number: shape parameter of the SSTd distribution. |
Object of class "SNorm"
This class is based on the code provided by the package fGarch by Diethelm Wuertz
Peter Ruckdeschel [email protected]
dsnorm, AbscontDistribution-class
(SN <- SNorm(mean = 1, sd = 1, xi = 0.5)) plot(SN)(SN <- SNorm(mean = 1, sd = 1, xi = 0.5)) plot(SN)
The skew normal distribution.
Objects can be created by calls of the form new("SNorm", mean, sd,xi).
More frequently they are created via the generating function
SNorm.
imgObject of class "Reals".
paramObject of class "SNormParameter".
rrgpd
ddgpd
ppgpd, but vectorized and with special treatment of
arguments lower.tail and log.p
qqgpd, but vectorized and with special treatment of
arguments lower.tail and log.p
gaps(numeric) matrix or NULL
.withArithlogical: used internally to issue warnings as to interpretation of arithmetics
.withSimlogical: used internally to issue warnings as to accuracy
.logExactlogical: used internally to flag the case where there are explicit formulae for the log version of density, cdf, and quantile function
.lowerExactlogical: used internally to flag the case where there are explicit formulae for the lower tail version of cdf and quantile function
Class "AbscontDistribution", directly.
Class "UnivariateDistribution", by class "AbscontDistribution".
Class "Distribution", by class "AbscontDistribution".
signature(object = "SNorm"): wrapped access method for
slot xi of slot param.
signature(object = "SNorm"): wrapped access method for
slot mean of slot param.
signature(object = "SNorm"): wrapped access method for
slot nu of slot param.
signature(x = "SNorm"): wrapped access method for
slot sd of slot param.
signature(object = "SNorm"): wrapped replace method for
slot xi of slot param.
signature(object = "SNorm"): wrapped replace method for
slot mean of slot param.
signature(object = "SNorm"): wrapped replace method for
slot nu of slot param.
signature(x = "SNorm"): wrapped replace method for
slot sd of slot param.
This class is based on the code provided by the package fGarch by Diethelm Wuertz
Peter Ruckdeschel [email protected]
dsnorm, AbscontDistribution-class
(SN <- SNorm(xi=2)) # SN is a skewed normal distribution with nu = 3. set.seed(1) r(SN)(1) # one random number generated from this distribution, e.g. -0.4037723 d(SN)(1) # Density of this distribution is 0.1914826 for x = 1. p(SN)(1) # Probability that x < 1 is 0.8374454. q(SN)(.1) # Probability that x < -1.137878 is 0.1. ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.) xi(SN) # shape of this distribution is 2. xi(SN) <- 2.5 # shape of this distribution is now 2.5. plot(SN)(SN <- SNorm(xi=2)) # SN is a skewed normal distribution with nu = 3. set.seed(1) r(SN)(1) # one random number generated from this distribution, e.g. -0.4037723 d(SN)(1) # Density of this distribution is 0.1914826 for x = 1. p(SN)(1) # Probability that x < 1 is 0.8374454. q(SN)(.1) # Probability that x < -1.137878 is 0.1. ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.) xi(SN) # shape of this distribution is 2. xi(SN) <- 2.5 # shape of this distribution is now 2.5. plot(SN)
The class of the parameter of an SNorm distribution.
Objects can be created by calls of the form new("SNormParameter", ...).
meanreal number: location parameter of a SNorm distribution.
sdreal number: scale parameter of a SNorm distribution.
namedefault name is “parameter of a SNorm distribution”.
xireal number: shape parameter of a SNorm distribution.
Class "Parameter", directly.
Class "OptionalParameter", by class "Parameter".
signature(object = "SNormParameter"): access method for
slot mean.
signature(object = "SNormParameter"): access method for
slot sd.
signature(object = "SNormParameter"): access method for
slot xi.
Peter Ruckdeschel [email protected]
P <- new("SNormParameter") mean(P) sd(P) xi(P) PP <- new("SNormParameter") mean(P) sd(P) xi(P) P
Generates an object of class "SSTd".
SSTd(mean = 0, sd = 1, nu = 5, xi = 1.5)SSTd(mean = 0, sd = 1, nu = 5, xi = 1.5)
mean |
real number: location parameter of the SSTd distribution. |
sd |
positive real number: scale parameter of the SSTd distribution |
xi |
positive real number: shape parameter of the SSTd distribution. |
nu |
real number larger than 2: degree of freedom parameter of the SSTd distribution. |
Object of class "SSTd"
This class is based on the code provided by the package fGarch by Diethelm Wuertz
Peter Ruckdeschel [email protected]
dsstd, AbscontDistribution-class
(ST <- SSTd(mean = 1, sd = 1, xi = 0.5)) plot(ST)(ST <- SSTd(mean = 1, sd = 1, xi = 0.5)) plot(ST)
The standardized skew Student-t distribution.
Objects can be created by calls of the form new("SSTd", mean, sd,xi).
More frequently they are created via the generating function
SSTd.
imgObject of class "Reals".
paramObject of class "SSTdParameter".
rrgpd
ddgpd
ppgpd, but vectorized and with special treatment of
arguments lower.tail and log.p
qqgpd, but vectorized and with special treatment of
arguments lower.tail and log.p
gaps(numeric) matrix or NULL
.withArithlogical: used internally to issue warnings as to interpretation of arithmetics
.withSimlogical: used internally to issue warnings as to accuracy
.logExactlogical: used internally to flag the case where there are explicit formulae for the log version of density, cdf, and quantile function
.lowerExactlogical: used internally to flag the case where there are explicit formulae for the lower tail version of cdf and quantile function
Class "AbscontDistribution", directly.
Class "UnivariateDistribution", by class "AbscontDistribution".
Class "Distribution", by class "AbscontDistribution".
signature(object = "SSTd"): wrapped access method for
slot xi of slot param.
signature(object = "SSTd"): wrapped access method for
slot mean of slot param.
signature(object = "SSTd"): wrapped access method for
slot nu of slot param.
signature(x = "SSTd"): wrapped access method for
slot sd of slot param.
signature(object = "SSTd"): wrapped replace method for
slot xi of slot param.
signature(object = "SSTd"): wrapped replace method for
slot mean of slot param.
signature(object = "SSTd"): wrapped replace method for
slot nu of slot param.
signature(x = "SSTd"): wrapped replace method for
slot sd of slot param.
This class is based on the code provided by the package fGarch by Diethelm Wuertz
Peter Ruckdeschel [email protected]
dsstd, AbscontDistribution-class
(ST <- SSTd(xi=2, nu = 3)) # ST is a skewed t distribution with xi = 2 and nu = 3. set.seed(1) r(ST)(1) # one random number generated from this distribution, e.g. -0.4432824 d(ST)(1) # Density of this distribution is 0.1204624 for x = 1. p(ST)(1) # Probability that x < 1 is 0.9035449. q(ST)(.1) # Probability that x < -0.4432824 is 0.1. ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.) nu(ST) # df of this distribution is 3. nu(ST) <- 4 # df of this distribution is now 4. plot(ST)(ST <- SSTd(xi=2, nu = 3)) # ST is a skewed t distribution with xi = 2 and nu = 3. set.seed(1) r(ST)(1) # one random number generated from this distribution, e.g. -0.4432824 d(ST)(1) # Density of this distribution is 0.1204624 for x = 1. p(ST)(1) # Probability that x < 1 is 0.9035449. q(ST)(.1) # Probability that x < -0.4432824 is 0.1. ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.) nu(ST) # df of this distribution is 3. nu(ST) <- 4 # df of this distribution is now 4. plot(ST)
The class of the parameter of an SSTd distribution.
Objects can be created by calls of the form new("SSTdParameter", ...).
meanreal number: location parameter of a SSTd distribution.
sdreal number: scale parameter of a SSTd distribution.
xireal number: shape parameter of a SSTd distribution.
nupositive number: the degree of freedom parameter of a SSTd distribution.
namedefault name is “parameter of a SSTd distribution”.
Class "Parameter", directly.
Class "OptionalParameter", by class "Parameter".
signature(object = "SSTdParameter"): access method for
slot mean.
signature(object = "SSTdParameter"): access method for
slot sd.
signature(object = "SSTdParameter"): access method for
slot xi.
signature(object = "SSTdParameter"): access method for
slot nu.
Peter Ruckdeschel [email protected]
P <- new("SSTdParameter") mean(P) sd(P) xi(P) nu(P) PP <- new("SSTdParameter") mean(P) sd(P) xi(P) nu(P) P
Generates a scaled object of class "Td";
the scale (sd) is chosen such that STd(nu=3, sd=1) has variance 1
independently from the degrees of freedom nu. This object
is of class "AffLinAbscontDistribution".
STd(mean = 0, sd = 1, nu = 5)STd(mean = 0, sd = 1, nu = 5)
mean |
real number: location parameter of the STd distribution. |
sd |
positive real number: scale parameter of the STd distribution |
nu |
real number larger than 2: degree of freedom parameter of the STd distribution. |
Object of class "STd"
This class is based on the code provided by the package fGarch by Diethelm Wuertz
Peter Ruckdeschel [email protected]
dstd, AbscontDistribution-class
(ST <- STd(mean = 1, sd = 1, nu = 3)) plot(ST)(ST <- STd(mean = 1, sd = 1, nu = 3)) plot(ST)