cmpp (version 0.0.1)

cdf_gomp: Compute the CDF of the Gompertz Distribution

Description

Calculates the cumulative distribution function (CDF) of the Gompertz distribution for given input values and parameters.

Usage

cdf_gomp(x, alpha, beta)

Value

A numeric vector of the CDF values for each input in x.

Arguments

x

A numeric vector of non-negative input values (e.g., failure times).

alpha

A positive numeric value representing the shape parameter.

beta

A positive numeric value representing the scale parameter.

Details

The Gompertz distribution is commonly used in survival analysis and reliability studies. Ensure that alpha and beta are positive for meaningful results.

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)
x <- c(1, 2, 3)
alpha <- 0.5
beta <- 0.1
lapply(x, cdf_gomp, alpha = alpha, beta = beta) |> unlist()