Gadget3 random effects likelihood actions — likelihood

Add likelihood components for random effects

g3l_random_dnorm(
        nll_name,
        param_f,
        mean_f = 0,
        sigma_f = 1,
        log_f = TRUE,
        period = 'auto',
        nll_breakdown = FALSE,
        weight = substitute(
            g3_param(n, optimise = FALSE, value = 1),
            list(n = paste0(nll_name, "_weight"))),
        run_at = g3_action_order$likelihood)

g3l_random_walk(
        nll_name,
        param_f,
        sigma_f = 1,
        log_f = TRUE,
        period = 'auto',
        nll_breakdown = FALSE,
        weight = substitute(
            g3_param(n, optimise = FALSE, value = 1),
            list(n = paste0(nll_name, "_weight"))),
        run_at = g3_action_order$likelihood)

Arguments

param_f: A formula representing the value to apply dnorm to. Invariably a g3_param for g3l_random_dnorm, a g3_param_table with cur_year for g3l_random_walk.
mean_f: A formula representing mean in dnorm.
sigma_f: A formula representing sigma in dnorm.
log_f: A formula representing log in dnorm.
period: When dnorm should be recalculated. Once per year every step, or single for once. The default, auto, will assume the input is generated by g3_parameterized and will derive the most appropriate option.
nll_name: Character string, used to define the variable name for dnorm output.
nll_breakdown: Should the nll report be broken down by time? TRUE / FALSE
weight: Weighting applied to this likelihood component.
run_at: Integer order that actions will be run within model, see g3_action_order.

Details

The model report will contain nll_random_dnorm_dnorm_lin__dnorm, the results of applying dnorm. If nll_breakdown is TRUE, this will be an array with one entry per timestep.

Value

g3l_random_dnorm

An action (i.e. list of formula objects) that will...

On the final model step, calculate dnorm(param_f, mean_f, sigma_f) & add to nll

g3l_random_walk

An action (i.e. list of formula objects) that will...

Calculate dnorm(param_f, previous param_f, sigma_f) (at final year if period = year)
Add to nll.

Examples

library(magrittr)

likelihood_actions <- list(
    # Calculate dnorm() for the dnorm_log parameter
    g3l_random_dnorm('dnorm_log',
        g3_parameterized('dnorm_log', value = 0, random = TRUE),
        mean_f = 0),

    # Treat the walk_year.xxxx parameters as a random walk
    g3l_random_walk('walk_year',
        g3_parameterized('walk_year', by_year = TRUE, value = 0, random = TRUE))
)