NonStandardT

dnst

pnst

qnst

rnst

x, q

degrees of freedom (&gt; 0, maybe non-integer). <code>df = Inf</code> is allowed.

vector of positive valued scale parameters.

sigma

logical; if TRUE, probabilities p are given as log(p).

log, log.p

logical; if TRUE (default), probabilities are \(P[X \le x]\)
otherwise, \(P[X &gt; x]\).

lower.tail

number of observations. If <code>length(n) &gt; 1</code>,
the length is taken to be the number required.

Probability mass function, distribution function and random generation
for non-standard t-distribution. Non-standard t-distribution besides
degrees of freedom \(\nu\), is parametrized using additional parameters
\(\mu\) for location and \(\sigma\) for scale (\(\mu=0\) and
\(\sigma = 1\) for standard t-distribution).

distribution

Density, distribution function, quantile function
and random generation for a number of univariate
and multivariate distributions. This package implements the
following distributions: Bernoulli, beta-binomial, beta-negative
binomial, beta prime, Bhattacharjee, Birnbaum-Saunders,
bivariate normal, bivariate Poisson, categorical, Dirichlet,
Dirichlet-multinomial, discrete gamma, discrete Laplace,
discrete normal, discrete uniform, discrete Weibull, Frechet,
gamma-Poisson, generalized extreme value, Gompertz,
generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t,
Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy,
Laplace, logarithmic, Lomax, multivariate hypergeometric,
multinomial, negative hypergeometric, non-standard t,
non-standard beta, normal mixture, Poisson mixture, Pareto,
power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam,
slash, triangular, truncated binomial, truncated normal,
truncated Poisson, Tukey lambda, Wald, zero-inflated binomial,
zero-inflated negative binomial, zero-inflated Poisson.

NonStandardT: Non-standard t-distribution

Description

Usage

Arguments

See Also

Examples