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1 Introduction
The Sujatha distribution, introduced by Shanker (2016), is a one-parameter lifetime distribution that has been successfully applied to lifetime, reliability, biological and engineering data. The SujathaDist package provides computational tools for distributional analysis, random number generation, parameter estimation and goodness-of-fit assessment.
2 Installation install.packages(“remotes”)
remotes::install_github(“hosenur72/SujathaDist”)
3 Loading the package library(SujathaDist)
4 Distribution functions
Explain
Density Distribution Quantile Random generation
Example
theta <- 2
dsujatha(1, theta)
psujatha(1, theta)
qsujatha(.5, theta)
rsujatha(10, theta)
5 Visualization
Include plots such as:
curve(dsujatha(x,2), from=0, to=10, lwd=2)
and
curve(psujatha(x,2), from=0, to=10, lwd=2)
6 Random sample generation set.seed(123)
x <- rsujatha(1000,2)
summary(x) 7 Parameter estimation fit <- fitsujatha(x)
summary(fit)
Explain:
estimate standard error confidence interval
8 Goodness-of-fit gofsujatha(fit)
Discuss:
Log-likelihood AIC BIC KS statistic p-value
9 Complete example
Provide a workflow from simulation to model fitting:
set.seed(123)
x <- rsujatha(100)
fit <- fitsujatha(x)
summary(fit)
gofsujatha(fit)
10 References
Include:
Prodhani, H. R. (2026). SujathaDist: Statistical Methods for the Sujatha Distribution. R package version 1.0.0. Shanker, R. (2016). Sujatha Distribution and its Applications. Statistics in Transition New Series, 17(3), 391–410.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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