non-parametric-statistics

TARGENE/TMLE.jl

A pure Julia implementation of the Targeted Minimum Loss-based Estimation

nt-williams/simul

:package: Simultaneous Confidence Bands Based on the Efficient Influence Function and Multiplier Bootstrap :books: :crystal_ball: :satellite:

S-razmi/Hands-on

Hands-on Instructions on Different courses

Mamba413/Nonparametric-Statistical-Inference-via-Metric-Distribution-Function-in-Metric-Spaces

Reproducible materials for Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces (JASA, 2023+)

sghosh89/BIVAN

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

songlab-cal/flinty

A Simple and Flexible Test of Sample Exchangeability with Applications to Statistical Genomics

tnathu-ai/Hypothesis-Testing-Crosfit-Case-Study

Hypothesis Testing CrossFit Game 2015

andreehrlich/individualized-treatment-survival

MSc Thesis: Non-Parametric Estimation of Optimal Individualized Treatment Rules for Survival Data

Goodfeelings/spring-2024-comp-intensive-stats-projects-02

Computer Intensive Stats - Project 02

JamesHotniel78/Median-Test-in-R-Software

Median Test in R Software

kapshaul/CT-medical-imaging

The Expectation Maximization (EM) algorithm is used to reduce Poisson noise in CT images. The repository provides derivations and evaluations with the Cramer-Rao Lower Bound (CRLB).

MalekYaich/Density-estimation-

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.

rmehta1987/CoZINB

Correlated Zero Inflated Negative Binomial Process

AbrahamHussein/STAT-523

Developed a function in R to compute the Cramér–von Mises test statistic(s) in R as no packages were readily available.

Arekflo2002/MetodyNieparametryczneStatystyka_Rozwiazania

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).

davidblakneymoore/The-Shared-Area-Under-Probability-Distribution-Curves-Test

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.

dorisyan1122/Non-Paramatric-Testing

Program Evaluation with Non-Parametric Statistics and Hypothesis Testing

ebjaime/European-Green-Deal-Analysis

An analysis of the European Renewable Transition.

EdaYaren/NonParametric

Parametrik olmayan istatistiksel yöntemler dersinin ödevi

hammerdirt-analyst/landuse

Using topographic attributes to identify zones of accumulation. Based on count data using EU protocol. Submitted for peer review.

hinc-b/UniProject_NonParametricModel

Project scope: Prediction if the bank's client will or will not leave the bank.

janasatvika/Hyperparameter-tuning-with-GridSearchCV

kasia-kobalczyk/mystatlearn

Accessible implementation of statistical learning algorithms, non-parametric and high-dimensional methods.

Marklong7/FeatureAlignment

This is an R package for feature alignment issues in vertical federated learning

Shalini-cmd/Statistics-Exploration-Reasoning

All my R code used for statistical analyses - Hypothesis Testing, t-tests, etc.

BioStatBioComp/Hands-on-Biostatistics-Workshop-2021

Materials of the Hands-on Biostatistics 2021 workshop

kamrul69/Non-parametric-statistics-tests-Beginner-to-Advanced

1. 1-sample sign test 2. 1-sample Wilcoxon test. 3. Wilcoxon test for paired data. 4. Mann-Whitney test. 5. Mood's median test. 6. Kruskal Wallis test. 7. Friedman test.

sebasr0/Estadistica-No-Parametrica-Regresion-Tests-EstadOrdenados

Análisis del Taller de Estadística No Paramétrica. Incluye modelos robustos y no paramétricos, estimación con KDE, pruebas estadísticas (Mann-Whitney U), y detección de outliers. Comparación de regresión RLM, RANSAC, y Kernel. Código para análisis, visualizaciones y resultados. - Modelos robustos y no paramétricos - KDE y análisis de distribución