estimate_parameters: Estimate Model Parameters Using Optimization

In cmpp: Direct Parametric Inference for the Cumulative Incidence Function in Competing Risks

Estimate Model Parameters Using Optimization

Description

This function estimates the parameters of a model by minimizing the negative log-likelihood function using the specified optimization method. It utilizes the optim() function in R, with the provided initial parameter values and gradient computation. The optimization method can be specified, with "BFGS" being the default.

Usage

estimate_parameters(initial_params = rep(0.01, 4), optimMethod = 'BFGS')

Arguments

initial_params	A numeric vector of initial parameter values to start the optimization. Default is a vector of four values, all set to 0.01.
optimMethod	A character string specifying the optimization method to use. The default is "BFGS". See ?optim for a list of available methods.

Details

The estimate_parameters function performs parameter estimation by minimizing the negative log-likelihood function using the chosen optimization method. The function requires an initial guess for the parameters (a numeric vector) and will optimize the log-likelihood function. The optimization also takes into account the gradient of the log-likelihood function, which is computed using the compute_grad function. The result of the optimization is an object of class optim containing the estimated parameters and other details of the optimization process.

The optimization method can be specified via the optimMethod argument. The default method is "BFGS", but any method supported by R's optim() function (such as "Nelder-Mead", "CG", etc.) can be used.

Value

An optim object containing the optimization results, including the estimated parameters, value of the objective function at the optimum, and other optimization details.

See Also

stats::optim for more details on optimization methods and usage.

Examples

library(cmpp)
data("fertility_data")
Nam <- names(fertility_data)
fertility_data$Education
datt <- make_Dummy(fertility_data, features = c("Education"))
datt <- datt$New_Data 
datt['Primary_Secondary'] <- datt$`Education:2`
datt['Higher_Education'] <- datt$`Education:3`
datt$`Education:2` <- datt$`Education:3` <- NULL
datt2 <- make_Dummy(datt, features = 'Event')$New_Data
d1 <- datt2$`Event:2`
d2 <- datt2$`Event:3`
feat <- datt2[c('age', 'Primary_Secondary', 'Higher_Education')] |> 
   data.matrix()
timee <- datt2[['time']]
Initialize(feat, timee, d1, d2, 1e-10)
# Estimate model parameters using default initial values and the BFGS method
result <- estimate_parameters()
print(result)

cmpp documentation built on June 8, 2025, 11:39 a.m.