Probabilistic Learning for mlr3
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Updated
Jun 27, 2024 - R
Probabilistic Learning for mlr3
📦 R/haldensify: Highly Adaptive Lasso Conditional Density Estimation
An R package for kernel density estimation with parametric starts and asymmetric kernels.
This is the R code for several common non-parametric methods (kernel est., mean regression, quantile regression, boostraps) with both practical applications on data and simulations
Sub-package of spatstat containing code for linear networks
R package for Random Encounter Modelling
estimate density from samples of population using maximum entropy approach
A R Package to find Optimal Bandwidth for Kernel Density Estimation using new methods based on K-Fold Maximum Likelihood and AIC.
Generalized Score Matching
Code and documentation from density UQ review paper.
This package is the result of my course project on density estimation.
Code and Documentation for Functional Regression on Densities of Observations (FRODO)
course sub-material for statistical computing class (2021 Fall)
EMMIX fits the data into the specified multivariate mixture models via the EM Algorithm.
R interface for estimated kernel densities comparisons
Code for the arXiv preprint:2206.05227
Code used for my undergraduate thesis "Income Inequality in Europe and Russia: Cross-Countries Analysis"
This repository contains code to perform the wildlife density modelling approach outlined in Houldcroft et al. (2024).
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