Collection of stats, modeling, and data science tools in Python and R.
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Updated
Jul 6, 2023 - HTML
Collection of stats, modeling, and data science tools in Python and R.
distfit is a python library for probability density fitting.
benfordslaw is about the frequency distribution of leading digits.
APEXSENSUN is a package in R for performing uncertainty and sensitivity analysis for the APEX model.
missCompare R package - intuitive missing data imputation framework
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
Implementing Unif(0,1) Pseudo Random Generators & performing Statistical Tests on them
A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical research
Samples generations using discrete probability and Kolmogorov-Sirmnov test
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.
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…
A simple, vectorized implementation of the two-sample Kolmogorov-Smirnov test in PyTorch.
Enhancing Statistical Tests: Integrating Automation and Visualization for Optimal Data Analytics
An analysis and classification model on Power Outages.
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)
Produce ROC, Concordance, KS, Calibration, Lift curve, Lift table for a binary classifier
Анализ датасета по суицидам в Шаньдуне.
This repository contains data science tools and methods, and my take and notes on some of them
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.
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