CIF_res1 {cmpp}R Documentation

Compute Cumulative Incidence Function (CIF) Results

Description

This function estimates the parameters of the model, computes the Hessian matrix, and calculates the variances and p-values for the parameters. It ensures that the diagonal elements of the covariance matrix are positive.

Usage

CIF_res1(initial_params = rep(0.001, 4))

Arguments

initial_params

A numeric vector of initial parameter values to start the optimization. Default is rep(0.001, 4).

Details

This function performs the following steps:

Value

A data frame containing:

Params

The parameter names ("alpha1", "beta1", "alpha2", "beta2").

STD

The standard deviations of the parameters.

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)
initial_params <- c(0.001, 0.001, 0.001, 0.001)
result <- CIF_res1(initial_params)
print(result)


[Package cmpp version 0.0.2 Index]