add_base.mcgf_rs function

Add base model outputted from fit_base() to an mcgf_rs object.

## S3 method for class 'mcgf_rs'
add_base(x, fit_base_ls, fit_s_ls, fit_t_ls, sep = FALSE, old = FALSE, ...)

Arguments

• x: An mcgf_rs` object.

• fit_base_ls: Output from the fit_base() function.

• fit_s_ls: Pure spatial model outputted from the fit_base() function. Used only when sep = TRUE.

• fit_t_ls: Pure temporal model outputted from the fit_base()

  function. Used only when sep = TRUE.

• sep: Logical; TRUE if spatial and temporal models are fitted separately.

• old: Logical; TRUE if the old base model needs to be kept. The lag and horizon of the new model are assumed to be the same as that of the old model.

• ...: Additional arguments. Not in use.

Returns

x with newly added attributes of the base model.

Details

After fitting the base model by fit_base(), the results can be added to x by add_base(). To supply the base model directly, use base<- to add the base model; the value must contain the same output as add_base.mcgf() or add_base.mcgf_rs().

Examples

data(sim2)
sim2_mcgf <- mcgf_rs(sim2$data, dists = sim2$dists, label = sim2$label)
sim2_mcgf <- add_acfs(sim2_mcgf, lag_max = 5)
sim2_mcgf <- add_ccfs(sim2_mcgf, lag_max = 5)

# Fit a regime-switching pure spatial model
fit_spatial <-
    fit_base(
        sim2_mcgf,
        lag_ls = 5,
        model_ls = "spatial",
        par_init_ls = list(c(c = 0.00005, gamma = 0.5)),
        par_fixed_ls = list(c(nugget = 0))
    )

# Fit a regime-switching pure temporal model
fit_temporal <-
    fit_base(
        sim2_mcgf,
        lag_ls = 5,
        model_ls = "temporal",
        par_init_ls = list(
            list(a = 0.8, alpha = 0.8),
            list(a = 0.1, alpha = 0.1)
        )
    )

# Store the fitted models to 'sim2_mcgf'
sim2_mcgf <- add_base(sim2_mcgf,
    fit_s_ls = fit_spatial,
    fit_t_ls = fit_temporal,
    sep = TRUE
)

# Fit a regime-switching separable model
fit_sep <- fit_base(
    sim2_mcgf,
    lag_ls = 5,
    model_ls = "sep",
    par_init_ls = list(list(
        c = 0.00005,
        gamma = 0.5,
        a = 0.5,
        alpha = 0.5
    )),
    par_fixed_ls = list(c(nugget = 0))
)

# Store the newly fitted model, and keep the old fit
sim2_mcgf <- add_base(sim2_mcgf, fit_base_ls = fit_sep, old = TRUE)
model(sim2_mcgf, model = "base", old = TRUE)

See Also

Other functions on fitting an mcgf_rs: add_lagr.mcgf_rs(), fit_base.mcgf_rs(), fit_lagr.mcgf_rs(), krige.mcgf_rs(), krige_new.mcgf_rs()