View source: R/canonical_mixture_constructors.R
Logitnormal.Mixture | R Documentation |
Create a Mixture Univariate Logit-Normal Distributions
Logitnormal.Mixture(
meanslogit,
sdslogit,
weights = 1,
lower = 0,
upper = 1,
var.name = NULL
)
meanslogit , sdslogit |
The means and standard deviations (on the logit scale) of the components of the 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 logit scale), if this is a bounded distribution (the same bounds apply for all components of the mixture) |
Other Canonical Mixture Distribution Constructors:
Lognormal.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()
,
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.Distribution()
,
Transformed.Normal.Mixture()
,
Uniform.Distribution()
,
Univariate.Canonical.Distribution()
,
join.distributions()
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