Official AFNI source and documentation
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Updated
May 23, 2024 - C
Official AFNI source and documentation
pure-Python HistFactory implementation with tensors and autodiff
R package for statistical inference using partially observed Markov processes
R package for score matching by automatic differentiation
Mobile Games A/B Testing Analysis
Estimagic is a Python package for nonlinear optimization with or without constraints. It is particularly suited to solve difficult nonlinear estimation problems. On top, it provides functionality to perform statistical inference on estimated parameters.
Personal notes during reading Statistics with R by Jenine K. Harris, 1st ed. (2019)
Analysis of bus delays data from TTC (Toronto Transit Commission). So far we concluded that there is a statistically signigificant difference in number of delays between days with good weather and bad weather within the "Mechanical" and "General" delay reasons. More details in Jupyter Notebooks.
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
A descriptive and inferential statistical analysis from the Kaggle database on the data collected by an IoT smoke detection device. Machine learning techniques were also used to help build this smart device, increasing its accuracy.
An R-package of teaching financial machine learning
For Data Enthusiasts Statistics Cheatsheet 2024
A comprehensive guide to applied econometrics and causal inference in R. Discusses Randomized Controlled Trials, Instrumental Variables, Regression Discontinuity Design, and Difference-in-Differences.
Statistical inference on machine learning or general non-parametric models
Estimating route conditional travel time and its uncertainty.
In this project, we will construct deep learning models from scratch using NumPy , including linear regression, logistic regression, and neural networks. we also converge parameter estimation, back-propagation, and statistical inference.
Inference Tools for SciViews::R
Statistics tools and utilities.
Predicting Absolute and Relative Abundance by Modeling Efficiency to Derive Intervals and Concentrations
Sub-package of spatstat containing code for linear networks
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