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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.

Usage

point_estimates(x, FUN = mean)

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)
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#> Computing log-likelihood
point_estimates(model)
#> alpha : double vector of length 2 
#> 
#> 2.1268 2.2299
#> 
#> 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 
#> 
#> 2.1029 2.2128
#> 
#> 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
#>