Transformed.Normal.Distribution: Create a Distribution of a Random Variable that is Normal...

View source: R/univariate_canonical_constructors.R

Transformed.Normal.DistributionR Documentation

Create a Distribution of a Random Variable that is Normal after an arbitrary transformation

Description

Create a Distribution of a Random Variable that is Normal after an arbitrary transformation

Usage

Transformed.Normal.Distribution(
  mean = 0,
  sd = 1,
  transformation = NULL,
  lower = -Inf,
  upper = Inf,
  var.name = NULL
)

Arguments

mean, sd

The mean and standard deviation of the random variable (after transformation has been applied)

lower, upper

The lower and the upper bounds, if this is a bounded distribution. The bounds are on the ORIGINAL scale (before transformation).

var.name

The name of the single variable in the distribution, or NULL if no name is specified

See Also

Other Univariate Canonical Distribution Constructors: Bernoulli.Distribution(), Beta.Distribution(), Binomial.Distribution(), Canonical.Mixture.Distribution(), Logitnormal.Distribution(), Logituniform.Distribution(), Lognormal.Distribution(), Loguniform.Distribution(), Normal.Distribution(), Uniform.Distribution(), Univariate.Canonical.Distribution()

Other Distribution Constructors: Autoregressive.Multivariate.Normal.Distribution(), Bernoulli.Distribution(), Beta.Distribution(), Binomial.Distribution(), Canonical.Mixture.Distribution(), Compound.Symmetry.Multivariate.Normal.Distribution(), Constant.Distribution(), Discrete.Set.Distribution(), Empiric.Distribution(), Logitnormal.Distribution(), Logitnormal.Mixture(), Logituniform.Distribution(), Lognormal.Distribution(), Lognormal.Mixture(), Loguniform.Distribution(), Multivariate.Correlated.Uniform.Distribution(), Multivariate.Logitnormal.Distribution(), Multivariate.Lognormal.Distribution(), Multivariate.Normal.Distribution(), Normal.Distribution(), Normal.Mixture(), Smoothed.Empiric.Distribution(), Transformed.Multivariate.Normal.Distribution(), Transformed.Normal.Mixture(), Uniform.Distribution(), Univariate.Canonical.Distribution(), join.distributions()


tfojo1/distributions documentation built on July 27, 2024, 3:29 p.m.