development

Robust and Flexible Model-Based Clustering for Data Sets with Missing Values at Random

Large-Scale Hypothesis Testing by Variance Mixing

Analysis and Exploration of Mixed Microbial Genomic Samples

Variable Length Markov Chains with Covariates

Unconstrained Numerical Optimization Algorithms

Dynamic Multi-Species Size Spectrum Modelling

Multivariate Joint Models with 'bamlss'

Statistical Classification

2D and 3D Movement-Based Kernel Density Estimates (MKDEs)

Descriptive Statistics

Matrix Kendall's Tau and Matrix Elliptical Factor Model

Kinetic Evaluation of Chemical Degradation Data

Inferential Statistics

Maximum Kernel Likelihood Estimation

A Modern K-Means (MKMeans) Clustering Algorithm

Miscellaneous Functions from M. Kohl

Multiple Knapsack Problem Solver

Omics Data Analysis

Power Analysis and Sample Size Calculation

Efficient Multi-Level k-Circulant Supersaturated Designs

Variational Autoencoder Models for IRT Parameter Estimation

Abstract Classes for Building 'scikit-learn' Like API

Machine Learning Benchmark Problems

Create 'ggplot2' and 'gt' Visuals with Major League Baseball Logos

Major League Baseball Player Statistics Calculator

Latent Class Item Response Theory (LC-IRT) Models under Within-Item Multidimensionality

Maximum Likelihood Conjoint Measurement

Classification Models with Copula Functions

Collection of Machine Learning Datasets for Supervised Machine Learning

Exploratory Data Analysis and Manipulation of Multi-Label Data Sets

Maximum Likelihood Difference Scaling

Maximum Likelihood Estimation of Various Univariate and Multivariate Distributions

Machine Learning Algorithms with Unified Interface and Confusion Matrices

Asymptotic Efficient Closed-Form Estimators for Multivariate Distributions

Computation of the MLE for Bivariate Interval Censored Data

Maximum Likelihood Estimates of Gaussian Processes

MLE for Normally Distributed Data Censored by Limit of Detection

Multilevel Exponential-Family Random Graph Models

Machine Learning Model Evaluation

Machine Learning Experiments

Machine Learning Foundations

Iterative Proportional Fitting Algorithms for Nested Structures

Machine Learning Forest Simulator

Datasets for Use with Salvan, Sartori and Pace (2020)

Multi-Layer Group-Lasso

Multilevel Index of Dissimilarity

Single and Multiple Imputation with Automated Machine Learning

R6-Based ML Learners for 'mlexperiments'

Multilevel Mediation Analysis

Multi-Level Monte Carlo

Machine Learning Evaluation Metrics

Multilevel/Mixed Model Helper Functions

Maximum Likelihood Multiple Imputation

Maximum Likelihood Estimation of DNA Methylation and Hydroxymethylation Proportions

Model Selection in Multivariate Longitudinal Data Analysis

Estimating Frequencies, Prevalence and Multiplicity of Infection

Power Analysis and Data Simulation for Multilevel Models

Examples from Multilevel Modelling Software Review

Multilevel Monitoring System Data for Wells in the USGS INL Aquifer Monitoring Network

Multi-Level Model Assessment Kit

Machine Learning Algorithms for Multivariate Time Series

Practical Multilevel Modeling

Bayesian Model Averaging for Multinomial Logit Models

'Rcpp' Integration for the 'mlpack' Library

Maximum Likelihood Estimation of the Niche Preemption Model

Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains)

A Power Analysis Toolbox to Find Cost-Efficient Study Designs

Algorithms for Class Distribution Estimation

Machine Learning in R

Batch Experiments for 'mlr3'

Analysis and Visualisation of Benchmark Experiments

Cluster Extension for 'mlr3'

Collection of Machine Learning Data Sets for 'mlr3'

Data Base Backend for 'mlr3'

Fairness Auditing and Debiasing for 'mlr3'

Extending 'mlr3' to Functional Data Analysis

Filter Based Feature Selection for 'mlr3'

Feature Selection for 'mlr3'