This is the newest member of the spatstat package family.
It contains code for estimation of univariate probability distributions.
You are viewing the GitHub repository which holds
the latest development version of spatstat.univar.
For the latest public release on CRAN, click the green badge above.
spatstat.univar contains code for
estimation of univariate probability distributions, including:
- weighted distributions and weighted statistics including weighted empirical cumulative distributions, weighted median, weighted quantiles, calculating the CDF from a density estimate;
- estimation for right-censored data including Kaplan-Meier, reduced-sample and other estimators of the cumulative distribution function and hazard function from right-censored data;
- quantiles including calculation of quantiles from an empirical cumulative distribution or a kernel density estimate;
- kernel density estimation for one dimensional probability densities, including fixed- and variable-bandwidth kernel estimators, and boundary corrections for densities restricted to the positive half-line;
- kernels including calculation of the probability density, cumulative distribution function, quantiles, random generation, moments and partial moments of the standard smoothing kernels;
- heat kernel: calculation of the one-dimensional heat kernel in an interval;
- integration: Numerical integration including Stieltjes integrals and indefinite integrals.
Some of the code has been extracted from spatstat.geom,
spatstat.random and spatstat.explore, while some is new.
This repository contains the development version of
spatstat.univar. The easiest way to install the development version
is to start R and type
repo <- c('https://spatstat.r-universe.dev', 'https://cloud.r-project.org')
install.packages("spatstat.univar", dependencies=TRUE, repos=repo)To install the latest public release of spatstat.univar,
type
install.packages("spatstat.univar")