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30 search results found

Teaching ⭐ 802

Teaching Materials for Dr. Waleed A. Yousef

Generalized linear models in Julia

Statsbase.jl ⭐ 559

Basic statistics for Julia

Mixedmodels.jl ⭐ 390

A Julia package for fitting (statistical) mixed-effects models

Spatstat ⭐ 172

Umbrella package of the 'spatstat' family................

Appelpy ⭐ 124

Applied Econometrics Library for Python

Archmodels.jl ⭐ 81

A Julia package for estimating ARMA-GARCH models.

Django Ai ⭐ 69

Artificial Intelligence for Django

Supplementary package for "Spatio-Temporal Statistics with R" by C.K. Wikle, A. Zammit-Mangion, and N. Cressie

Conjugate_prior ⭐ 51

Implementation of the conjugate prior table for Bayesian Statistics

PF: a header only template library for fast particle filtering!

Autodiff ⭐ 34

Autodiff is a numerical library for the Go programming language that supports automatic differentiation. It implements routines for linear algebra (vector/matrix operations), numerical optimization and statistics

Latent Variable Models in R https://kkholst.github.io/lava/

Metida.jl ⭐ 24

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.

Visualisation for statistical models.

Tidystats ⭐ 18

R package to save and report the output of statistical models.

Fit, evaluate, and visualise generalised additive models (GAMs) in native Julia

Lctmtools ⭐ 12

Latent Class Trajectory Models: An R Package

A Bayesian model of series convergence using Gaussian sums

Generalized Additive Models ⭐ 10

Generalized Additive Models in Python.

Cegpy (/segpaɪ/) is a Python package for working with Chain Event Graphs. It supports learning the graphical structure of a Chain Event Graph from data, encoding of parametric and structural priors, estimating its parameters, and performing inference.

A quick reference for how to run many models in R.

A library for Time-Series exploration, analysis & modelling.

Machine Learning ⭐ 7

Fundamentals & projects

Shinybrms ⭐ 7

An R package providing a GUI ('shiny' app) for the R package 'brms'.

Nba Models ⭐ 6

The goal of this project is to create a series of statistical models regarding NBA statistics, with the ultimate goal of implementing a website predicting odds for each major award and all star selections.

Mestimation.jl ⭐ 6

Methods for M-estimation of statistical models

Risk_calculation_using_backward_elimination_algorithm_in_life_insurance ⭐ 6

Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.

Python codes for the book, An Introduction to Statistical Learning with Applications in R (ISLR)

Python implementation of STATIS for analysis of several data tables

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