This function computes the point estimates of an RprobitB_fit.
Per default, the mean of the Gibbs samples is used as a point estimate.
However, any statistic that computes a single numeric value out of a vector of
Gibbs samples can be specified for FUN.
Arguments
- x
An object of class
RprobitB_fit.- FUN
A function that computes a single numeric value out of a vector of numeric values.
Value
An object of class RprobitB_parameter.
Examples
data <- simulate_choices(form = choice ~ covariate, N = 10, T = 10, J = 2)
model <- fit_model(data)
#> Computing sufficient statistics - 0 of 4
#> Computing sufficient statistics - 1 of 4
#> Computing sufficient statistics - 2 of 4
#> Computing sufficient statistics - 3 of 4
#> Computing sufficient statistics - 4 of 4
#> MCMC iteration - 1 of 1000
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#> Computing log-likelihood
point_estimates(model)
#> alpha : double vector of length 2
#> -1.55 -1.09
#>
#> C : NA
#>
#> s : NA
#>
#> b : NA
#>
#> Omega : NA
#>
#> Sigma : 1
#>
#> Sigma_full : 2 x 2 matrix of doubles
#> [,1] [,2]
#> [1,] 2 1
#> [2,] 1 1
#>
#>
#> beta : NA
#>
#> z : NA
#>
#> d : NA
#>
point_estimates(model, FUN = median)
#> alpha : double vector of length 2
#> -1.52 -1.07
#>
#> C : NA
#>
#> s : NA
#>
#> b : NA
#>
#> Omega : NA
#>
#> Sigma : 1
#>
#> Sigma_full : 2 x 2 matrix of doubles
#> [,1] [,2]
#> [1,] 2 1
#> [2,] 1 1
#>
#>
#> beta : NA
#>
#> z : NA
#>
#> d : NA
#>