Autoregressive.Multivariate.Normal.Distribution: Create a multivariate normal distribution with a Continuous...

View source: R/multivariate_constructors.R

Autoregressive.Multivariate.Normal.DistributionR Documentation

Create a multivariate normal distribution with a Continuous Autoregressive 1 (CAR-1) correlation structure

Description

Creates a distribution where all the variables, after arbitrary transformations, follow a normal distribution with a Continuous Autoregressive 1 (CAR-1) correlation structure

Usage

Autoregressive.Multivariate.Normal.Distribution(
  rho,
  times,
  mu = 0,
  sds = 1,
  lower = -Inf,
  upper = Inf,
  var.names = NULL,
  transformations = NULL
)

Arguments

rho

The autoregressive correlation coefficient

times

The times for each observation in the distribution. The correlation between any two observations at times t1 and t2 is rho^(abs(t1-t2))

mu, sds

The mean and standard deviation vectors. If given a scalar value, assumes that the mean/sd is the same for every variable in the distribution

lower

The upper and lower bounds for each variable (on the original scale, NOT the transformed scale). If only one value is given, assumed to apply to all variables in the distribution

upper

The upper and lower bounds for each variable (on the original scale, NOT the transformed scale). If only one value is given, assumed to apply to all variables in the distribution

var.names

The names of the variables in the distribution. If NULL, uses the names of mu, the row names of sigma, or the column names of sigma, in that order

transformations

Objects of class transformation to be applied to each variable. Can be either an object of class transformation, the character name of a defined transformation, or a list of transformation objects. If only one transformation is supplied, assumed to apply to all variables. If this is a named list, any variables missing transformation are assmed to not be transformed

See Also

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


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