Type: Package
Title: Fit Modified Weibull-Type Distributions
Version: 0.1.0
Description: Provides maximum likelihood estimation methods for eight modified Weibull-type distributions. It returns parameter estimates, log-likelihood, AIC, and BIC, and also supports model fitting, validation, and comparison across different distributional forms. These methods can be applied to reliability, survival, and lifetime data analysis, making the package useful for researchers and practitioners in statistics, engineering, and medicine. The following distributions are included: Rangoli2023, Peng2014, Lai2003, Xie1996, Sarhan2009, Rangoli2025, Mustafa2012, and Alwasel2009.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
Imports: stats
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-10-08 06:28:36 UTC; Reneuit
Author: Dr Ajaykumar Rangoli [aut, cre]
Maintainer: Dr Ajaykumar Rangoli <drajaykumarmr1008@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-10 20:10:02 UTC

Fit Modified Weibull-Type Distributions

Description

Fits eight modified Weibull-type distributions using maximum likelihood estimation. Returns estimates, log-likelihood, AIC, and BIC.

Usage

WeibullModiAMR(x, dist = "Alwasel2009")

Arguments

x

Numeric vector of positive data.

dist

Character; choose one of: "Rangoli2023", "Peng2014", "Lai2003", "Xie1996", "Sarhan2009", "Rangoli2025", "Mustafa2012", "Alwasel2009".

Value

A list containing:

estimates

Estimated parameters.

loglik

Maximized log-likelihood.

AIC

Akaike Information Criterion.

BIC

Bayesian Information Criterion.

Distributions

The following modified Weibull-type distributions are included in the package, along with their respective probability density functions (PDFs) and references:

Examples

# Load your package
library(WeibullModiAMR)

# Example: Fit Rangoli2023 distribution
x <- rexp(50, rate = 1)
res <- WeibullModiAMR(x, dist = "Rangoli2023")
print(res)