You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This repo is for copula based analysis on bivariate as well as multivariate data sets in ecology and related fields. For details and citation we refer to this publication: Ghosh et al., Advances in Ecological Research, vol 62,pp 409, 2020
The shared area under probability distribution curves test is a non-parametric alternative to the analysis of variance. It makes no assumptions about the data and it is not based on ranks, so information about absolute distances between data points is not lost.
So this is my final project for non-parametric methods in statistics. I work in Jupyter Notebook and extract solutions to HTML. I mainly test power of the selected tests(chi square, kolmogorov,etc.) depending on different variables(like deegres of freedom of the distribution or number of observations).
This project offers an R code implementation for estimating the density function using the kernel method. It explores different values of the parameters h and n to perform these estimations.