There are 0 repository under kolmogorov-smirnov topic.
Collection of stats, modeling, and data science tools in Python and R.
benfordslaw is about the frequency distribution of leading digits.
missCompare R package - intuitive missing data imputation framework
Python implementation of an extension of the Kolmogorov-Smirnov test for multivariate samples
A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical research
Computational predictions of protein attributes associated with COVID-19 using Data Science techniques
Code for testing Concept drift techniques on a real word dataset on a hexapod robot
APEXSENSUN is a package in R for performing uncertainty and sensitivity analysis for the APEX model.
An analysis and classification model on Power Outages.
Samples generations using discrete probability and Kolmogorov-Sirmnov test
Implementing Unif(0,1) Pseudo Random Generators & performing Statistical Tests on them
This repository contains data science tools and methods, and my take and notes on some of them
Machine Learning basics codes I wrote in 2020
Como descrever meus dados? Quais testes estatísticos devo usar? Síntese dos testes estatísticos (introdutórios) que podem ser usados em uma análise de dados em saúde.
Shandong suicide dataset analysis
Анализ датасета по суицидам в Шаньдуне.
This is an contrast of linear regression model, used to examine the association between the independent variable(category or contineous) with dependent variable(binary), which is an discrete outcome.
Produce ROC, Concordance, KS, Calibration, Lift curve, Lift table for a binary classifier
Built LDA and QDA models on variables obtained from Principal Component Analysis (PCA) and Kolmogorov-Smirnov (KS) and tuned by leave-one-out cross-validation (LOOCV) to predict fraudulent online advertising click traffic
Report findings from normality tests such as shapiro.test, ad.test, ols_normality_test.
Our team analyzed real data to help TFA optimize its corps matching process for placement acceptance and successful corps experiences. Finalists were selected in a multi-round process based on the degree to which they demonstrated.
Data Drift Analysis and Anomaly detection tools
Enthält statistische Tests auf Gleichverteilung und Monte-Carlo-Simulationen um diese zu vergleichen.
Enhancing Statistical Tests: Integrating Automation and Visualization for Optimal Data Analytics
A simple, vectorized implementation of the two-sample Kolmogorov-Smirnov test in PyTorch.
PCTSEA (Proteomics Cell Type Enrichment Analysis) is a tool designed to statistically determine which cell types are significatively enriched in an input set of proteins with certain relative expression values. This process is done by using a database of datasets of RNASeq expression values from single cells from which the cell type is known (or predicted).
Matlab implementation of the improved Peacock algorithm by Yuanhui Xiao.
Project of a coursework - Nonparametric Inference (M.Stat Semester 2) under the supervision of Prof. Isha Dewan. (Project Group : Uttaran Chatterjee, Adrija Saha, Shrayan Roy)
Analysis of two variables by nonparametric method
The Monte Carlo method and the Kolmogorov-Smirnov correspondence criterion for a generation task
SmoothTrend is a comprehensive time series analysis tool that utilizes Holt-Winters, Holt, and Simple Exponential Smoothing methods, as well as ARIMA/SARIMA modeling, to perform advanced trend analysis, stationarity testing, residual analysis, and forecasting.
R codes for Nonparametric Statistics
This repository contains baseconfigs & userconfigs, cGENIE outputs, Python scripts for data analysis, and figures associated with the Herho et al. (2024) manuscript.
Statistical analyses of the 2021 Albanian parliamentary elections