cdf_gomp {cmpp} | R Documentation |
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)
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.
Value
A numeric vector of the CDF 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, cdf_gomp, alpha = alpha, beta = beta) |> unlist()
[Package cmpp version 0.0.2 Index]