📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
-
Updated
Nov 14, 2024 - R
📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
R package for random forests model selection, inference, evaluation and validation
Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
Perform inference on algorithm-agnostic variable importance
The R wrapper to the fdaPDE library for physics-informed spatial and functional data analysis.
An R package for assumption-lean covariance matrix estimation in high dimensions
Chinese Restaurant Process Models for Regression and Clustering. Master branch contains latest stable build.
Nonparametric kernel density estimation, bandwidth selection, and other utilities for analyzing directional data
Robust estimations from distribution structures: Central moments.
R6-Based Flexible Framework for Permutation Tests
UW course projects
R Package providing functions to calculate pseudo-ranks and pseudo-rank based nonparametric test statistics.
An R package for determining groups of curves
Nonparametric analysis of 2020 US presidential elections.
This repository contains exploratory spatial data analysis (ESDA) functions and scripts. These functions are designed for geothermal spatial datasets, and are applicable to other spatial datasets.
A Dirichlet-multinomial mixture model-based approach for daily solar radiation classification
Is it possible to predict the popularity of a song based on its technical features? Which aspect of a song should an artist focus on to get more visibility? Could record labels or a new up-and-coming artist benefit from these data-driven and data-informed decisions?
The order-md algorithm is an adjustment of the order-m algorithm for estimating efficiency scores of decision making units (firms)
R codes for Nonparametric Statistics
The code interface is written in R, and for the sake of speed, most parts are written in C++. However, no prerequisite knowledge for both languages is required to run the code. An R file called runInfHMM.R sources all needed functions to compile and run the code.
Add a description, image, and links to the nonparametric-statistics topic page so that developers can more easily learn about it.
To associate your repository with the nonparametric-statistics topic, visit your repo's landing page and select "manage topics."