Calculate trend correlations based on latent factor loadings for mvgam models

This function uses samples of latent trends for each series from a fitted mvgam model to calculates correlations among series' trends

Usage

lv_correlations(object)

Arguments

object

list object of class mvgam

Value

A list object containing the mean posterior correlations and the full array of posterior correlations

Examples

# \donttest{
simdat <- sim_mvgam()
mod <- mvgam(y ~ s(season, bs = 'cc',
                  k = 6),
            trend_model = AR(),
            use_lv = TRUE,
            n_lv = 2,
            data = simdat$data_train,
            burnin = 300,
            samples = 300,
            chains = 2,
            silent = 2)
#> Warning in '/tmp/RtmpBC1K15/model_4ea86485fa6394b2bd06379ea36195d8.stan', line 23, column 31: Found
#>     int division:
#>       n_lv * (n_lv - 1) / 2
#>     Values will be rounded towards zero. If rounding is not desired you can
#>     write
#>     the division as
#>       n_lv * (n_lv - 1) / 2.0
#>     If rounding is intended please use the integer division operator %/%.
#> Warning in '/tmp/RtmpBC1K15/model-234f10d6f0bb.stan', line 23, column 33: Found
#>     int division:
#>       n_lv * (n_lv - 1) / 2
#>     Values will be rounded towards zero. If rounding is not desired you can
#>     write
#>     the division as
#>       n_lv * (n_lv - 1) / 2.0
#>     If rounding is intended please use the integer division operator %/%.
lvcors <- lv_correlations(mod)
names(lvcors)
#> [1] "mean_correlations"      "posterior_correlations"
lapply(lvcors, class)
#> $mean_correlations
#> [1] "matrix" "array" 
#> 
#> $posterior_correlations
#> [1] "list"
#> 
# }