ModelParamsNormal

ModelParamsNormal is the class for a bivariate normal model parameters, i.e. the mean vector, covariance matrix and precision matrix. The precision matrix is an inverse of the covariance matrix in the JAGS and it is computed internally by the object constructor function.

Usage

ModelParamsNormal(mean, cov)

.DefaultModelParamsNormal()

Arguments

mean

(numeric)
the prior mean vector.

cov

(matrix)
the prior covariance matrix. The precision matrix prec is internally calculated as an inverse of cov.

Slots

mean

(numeric)
the mean vector.

cov

(matrix)
the covariance matrix.

prec

(matrix)
the precision matrix, which is an inverse matrix of the cov.

Note

Typically, end users will not use the .ModelPAramsNormal() function.

See also

ModelLogNormal, LogisticNormalMixture.

Examples

ModelParamsNormal(mean = c(1, 6), cov = diag(2))
#> An object of class "ModelParamsNormal"
#> Slot "mean":
#> [1] 1 6
#> 
#> Slot "cov":
#>      [,1] [,2]
#> [1,]    1    0
#> [2,]    0    1
#> 
#> Slot "prec":
#>      [,1] [,2]
#> [1,]    1    0
#> [2,]    0    1
#>