Lognormal.Mixture: Create a Mixture of Univariate Log-Normal Distributions

In tfojo1/distributions:

Create a Mixture of Univariate Log-Normal Distributions

Description

Create a Mixture of Univariate Log-Normal Distributions

Usage

Lognormal.Mixture(
  meanslog = 0,
  sdslog = 1,
  weights = 1,
  lower = 0,
  upper = Inf,
  var.name = NULL
)

Arguments

meanslog, sdslog	The means and standard deviations (on the log scale) of the components of distribution
weights	The weights applied to each component of the mixture. Weights need not be normalized to sum to 1. If a scalar value is given, all components of the mixture will have the same weight
lower, upper	The lower and the upper bounds (on the original scale, NOT the log scale), if this is a bounded distribution (the same bounds apply for all components of the mixture)

See Also

Other Canonical Mixture Distribution Constructors: Logitnormal.Mixture(), Normal.Mixture(), Transformed.Normal.Mixture()

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(), 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.Distribution(), Transformed.Normal.Mixture(), Uniform.Distribution(), Univariate.Canonical.Distribution(), join.distributions()

tfojo1/distributions documentation built on June 1, 2025, 9:07 p.m.