sst-functions: Functions for Symmetric Student-t distribution

sst-functionsR Documentation

Functions for Symmetric Student-t distribution

Description

Functions for Symmetric Student-t distribution

Usage

dsst(x, mu = 0, s = 1, alpha = 0.5, nu = Inf, pars = NULL)

psst(q, mu = 0, s = 1, alpha = 0.5, nu = Inf, pars = NULL)

qsst(p, mu = 0, s = 1, alpha = 0.5, nu = Inf, pars = NULL)

rsst(n, mu = 0, s = 1, alpha = 0.5, nu = Inf, pars = NULL)

sstMoments(
  mu = 0,
  s = 1,
  alpha = 0.5,
  nu = Inf,
  pars = NULL,
  method = c("analytical", "numerical"),
  type = c("excess", "regular")
)

sstRawMoment(
  n,
  mu = 0,
  s = 1,
  alpha = 0.5,
  nu = Inf,
  pars = NULL,
  method = c("analytical", "numerical")
)

sstCentralMoment(
  n,
  mu = 0,
  s = 1,
  alpha = 0.5,
  nu = Inf,
  pars = NULL,
  method = c("analytical", "numerical")
)

sstInfoMat(pars)

sstMLE(
  data,
  start_pars = c(),
  fixed_pars = c(),
  solver = c("nlminb", "nloptr", "Rsolnp"),
  solver_control = list()
)

Arguments

x, q

vector of quantiles

mu

location parameter

s

scale parameter, s > 0

alpha

skewness parameter, 0 < alpha < 1

nu

degrees of freedom / tail parameter for the both tails, nu > 0

pars

a vector that contains mu, s, alpha, nu1, nu2, if pars is specified, mu, s, alpha, nu1, nu2 should not be specified

p

vector of probablilities

n

number of observations for random generation

method

method used to calculate the moment(s), one of 'analytical' and 'numerical'

type

type of kurtosis calculated, one of 'excess' and 'regular'

data

a univariate data object to be fitted

start_pars

a named numeric vector of starting parameters for the optimization algorithm, not all parameters are needed

fixed_pars

a named numeric vector of parameters to be kept fixed during the optimization routine, not all parameters are needed

solver

solver used for MLE, one of 'nlminb', 'nloptr', 'Rsolnp', default is 'nlminb'

solver_control

list of control arguments passed to the solver

Details

The SST functions are wrappers of their AST equivalent.

For most of the functions, they are implemented by simply setting nu1, nu2(AST) = nu(SST).

For sstFit, it is implemented by setting symmetric = TRUE.


dan9401/skewtDist documentation built on Jan. 6, 2025, 9:14 a.m.