pdf_gomp {cmpp}R Documentation

Compute the PDF of the Gompertz Distribution

Description

Calculates the probability density function (PDF) of the Gompertz distribution for given input values and parameters.

Usage

pdf_gomp(x, alpha, beta)

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 PDF provides the relative likelihood of a failure or event occurring at specific time points. Ensure that alpha and beta are positive for meaningful results.

Value

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

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, pdf_gomp, alpha = alpha, beta = beta) |> unlist()

[Package cmpp version 0.0.2 Index]