add_base.mcgf: Add base model outputted from 'fit_base()' to an 'mcgf'...

In mcgf: Markov Chain Gaussian Fields Simulation and Parameter Estimation

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

Description

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

Usage

## S3 method for class 'mcgf'
add_base(x, fit_base, fit_s, fit_t, sep = FALSE, old = FALSE, ...)

base(x) <- value

Arguments

x	An mcgf object.
fit_base	Output from the fit_base() function.
fit_s	Pure spatial model outputted from the fit_base() function. Used only when sep = TRUE.
fit_t	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.
...	Additional arguments. Not in use.
value	A list containing the base model as well as its parameters. It must contains the same output as add_base.mcgf() or add_base.mcgf_rs().

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 model, par_base, cor_base, lag, and horizon.

Value

x with newly added attributes of the base model.

See Also

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

Examples

data(sim1)
sim1_mcgf <- mcgf(sim1$data, dists = sim1$dists)
sim1_mcgf <- add_acfs(sim1_mcgf, lag_max = 5)
sim1_mcgf <- add_ccfs(sim1_mcgf, lag_max = 5)

# Fit a pure spatial model
fit_spatial <- fit_base(
    sim1_mcgf,
    model = "spatial",
    lag = 5,
    par_init = c(c = 0.001, gamma = 0.5),
    par_fixed = c(nugget = 0)
)
# Fit a pure temporal model
fit_temporal <- fit_base(
    sim1_mcgf,
    model = "temporal",
    lag = 5,
    par_init = c(a = 0.3, alpha = 0.5)
)

# Store the fitted models to 'sim1_mcgf'
sim1_mcgf <-
    add_base(sim1_mcgf,
        fit_s = fit_spatial,
        fit_t = fit_temporal,
        sep = TRUE
    )

# Fit a separable model
fit_sep <- fit_base(
    sim1_mcgf,
    model = "sep",
    lag = 5,
    par_init = c(
        c = 0.001,
        gamma = 0.5,
        a = 0.3,
        alpha = 0.5
    ),
    par_fixed = c(nugget = 0)
)
# Store the newly fitted model, and keep the old fit
sim1_mcgf <- add_base(sim1_mcgf, fit_base = fit_sep, old = TRUE)
model(sim1_mcgf, model = "base", old = TRUE)

mcgf documentation built on June 29, 2024, 9:09 a.m.