fit_model {calmr}

Fit model to data

Description

Obtain MLE estimates for model, given data.

Usage

fit_model(data, model_function, optimizer_options, file = NULL, ...)

Arguments

data

A numeric vector containing data to fit model against.

model_function

A function that runs the model and returns data.frame of value, organized as in data.

optimizer_options

A list with options for the optimizer, as returned by get_optimizer_opts.

file

A path to save the model fit. If the arguments to the fit call are found to be identical to those in the file, the model just gets loaded.

...

Extra parameters passed to the optimizer call.

Value

A CalmrFit object

Note

See the calmr_fits vignette for examples

See Also

get_optimizer_opts()

Examples

# Make some fake data
df <- data.frame(g = "g", p1 = "3A>(US)", r1 = TRUE)
pars <- get_parameters(df, model = "RW1972")
pars$alphas["US"] <- 0.9
exper <- make_experiment(df, parameters = pars, model = "RW1972")
res <- run_experiment(exper, outputs = "rs")
rs <- results(res)$rs$value

# define model function
model_fun <- function(p, ex) {
  np <- parameters(ex)
  np[[1]]$alphas[] <- p
  parameters(ex) <- np
  results(run_experiment(ex))$rs$value
}

# Get optimizer options
optim_opts <- get_optimizer_opts(
  model_pars = names(pars$alphas),
  ll = rep(.05, 2), ul = rep(.95, 2),
  optimizer = "optim", family = "identity"
)
optim_opts$initial_pars[] <- rep(.6, 2)

fit_model(rs, model_fun, optim_opts,
  ex = exper, method = "L-BFGS-B",
  control = list(maxit = 1)
)