All packages

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mhsmm — 0.4.21

Inference for Hidden Markov and Semi-Markov Models

mhtboot — 1.3.3

Multiple Hypothesis Test Based on Distribution of p Values

MHTdiscrete — 1.0.1

Multiple Hypotheses Testing for Discrete Data

MHTmult — 0.1.0

Multiple Hypotheses Testing for Multiple Families/Groups Structure

MHTrajectoryR — 1.0.1

Bayesian Model Selection in Logistic Regression for the Detection of Adverse Drug Reactions

mhurdle — 1.3-1

Multiple Hurdle Tobit Models

mi — 1.1

Missing Data Imputation and Model Checking

mi4p — 1.1

Multiple Imputation for Proteomics

MIAmaxent — 1.2.0

A Modular, Integrated Approach to Maximum Entropy Distribution Modeling

micar — 1.1.2

'Mica' Data Web Portal Client

micd — 1.1.1

Multiple Imputation in Causal Graph Discovery

mice — 3.16.0

Multivariate Imputation by Chained Equations

miceadds — 3.17-44

Some Additional Multiple Imputation Functions, Especially for 'mice'

miceafter — 0.5.0

Data and Statistical Analyses after Multiple Imputation

micEcon — 0.6-18

Microeconomic Analysis and Modelling

micEconAids — 0.6-20

Demand Analysis with the Almost Ideal Demand System (AIDS)

micEconCES — 1.0-2

Analysis with the Constant Elasticity of Substitution (CES) Function

micEconDistRay — 0.1-2

Econometric Production Analysis with Ray-Based Distance Functions

micEconIndex — 0.1-8

Price and Quantity Indices

micEconSNQP — 0.6-10

Symmetric Normalized Quadratic Profit Function

miceFast — 0.8.2

Fast Imputations Using 'Rcpp' and 'Armadillo'

micemd — 1.10.0

Multiple Imputation by Chained Equations with Multilevel Data

miceRanger — 1.5.0

Multiple Imputation by Chained Equations with Random Forests

michelRodange — 1.0.0

The Works (in Luxembourguish) of Michel Rodange

miclust — 1.2.8

Multiple Imputation in Cluster Analysis

micompr — 1.1.4

Multivariate Independent Comparison of Observations

miCoPTCM — 1.1

Promotion Time Cure Model with Mis-Measured Covariates

microbats — 0.1-1

An Implementation of Bat Algorithm in R

microbenchmark — 1.4.10

Accurate Timing Functions

microbial — 0.0.21

Do 16s Data Analysis and Generate Figures

MicrobiomeStat — 1.2

Statistical Methods for Microbiome Compositional Data

MicrobiomeSurv — 0.1.0

Biomarker Validation for Microbiome-Based Survival Classification and Prediction

microclass — 1.2

Methods for Taxonomic Classification of Prokaryotes

microcontax — 1.2

The ConTax Data Package

microCRAN — 0.9.0-1

Hosting an Independent CRAN Repository

microdatasus — 2.3.1

Download and Process 'DataSUS' Files

MicroDatosEs — 0.8.15

Utilities for Official Spanish Microdata

microdiluteR — 1.0.1

Analysis of Broth Microdilution Assays

microeco — 1.8.0

Microbial Community Ecology Data Analysis

microhaplot — 1.0.1

Microhaplotype Constructor and Visualizer

MicroMacroMultilevel — 0.4.0

Micro-Macro Multilevel Modeling

micromap — 1.9.8

Linked Micromap Plots

micromapST — 3.0.3

Linked Micromap Plots for U. S. and Other Geographic Areas

MicroMoB — 0.1.2

Discrete Time Simulation of Mosquito-Borne Pathogen Transmission

micromodal — 1.0.0

Create Simple and Elegant Modal Dialogs in 'shiny'

MicroNiche — 1.0.0

Microbial Niche Measurements

micronutr — 0.1.1

Determining Vitamin and Mineral Status of Populations

micropan — 2.1

Microbial Pan-Genome Analysis

microplot — 1.0-45

Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel'

microPop — 1.6

Process-Based Modelling of Microbial Populations

microseq — 2.1.6

Basic Biological Sequence Handling

microsimulation — 1.4.3

Discrete Event Simulation in R and C++, with Tools for Cost-Effectiveness Analysis

Microsoft365R — 2.4.0

Interface to the 'Microsoft 365' Suite of Cloud Services

microsynth — 2.0.44

Synthetic Control Methods with Micro- And Meso-Level Data

MicSim — 2.0.1

Performing Continuous-Time Microsimulation

MICsplines — 1.0

The Computing of Monotonic Spline Bases and Constrained Least-Squares Estimates

micsr — 0.1-1

Microeconometrics with R

micss — 0.1.5

Modified Iterative Cumulative Sum of Squares Algorithm

MiDA — 0.1.2

Microarray Data Analysis

midas — 1.0.1

Turn HTML 'Shiny'

midas2 — 1.1.0

Bayesian Platform Design with Subgroup Efficacy Exploration(MIDAS-2)

midasml — 0.1.10

Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data

midasr — 0.8

Mixed Data Sampling Regression

midastouch — 1.3

Multiple Imputation by Distance Aided Donor Selection

midfieldr — 1.0.2

Tools and Methods for Working with MIDFIELD Data in 'R'

midi — 0.1.0

Microstructure Information from Diffusion Imaging

MIDN — 1.0

Nearly Exact Sample Size Calculation for Exact Powerful Nonrandomized Tests for Differences Between Binomial Proportions

midrangeMCP — 3.1.1

Multiples Comparisons Procedures Based on Studentized Midrange and Range Distributions

miesmuschel — 0.0.4-1

Mixed Integer Evolution Strategies

mifa — 0.2.0

Multiple Imputation for Exploratory Factor Analysis

MigConnectivity — 0.4.7

Estimate Migratory Connectivity for Migratory Animals

migest — 2.0.4

Methods for the Indirect Estimation of Bilateral Migration

migraph — 1.3.4

Many Network Measures, Motifs, Members, and Models

migrate — 0.4.0

Create Credit State Migration (Transition) Matrices

migration.indices — 0.3.1

Migration Indices

MigrationDetectR — 0.1.1

Segment-Based Migration Detection Algorithm

migui — 1.3

Graphical User Interface to the 'mi' Package

miic — 1.5.3

Learning Causal or Non-Causal Graphical Models Using Information Theory

MIIPW — 0.1.1

IPW and Mean Score Methods for Time-Course Missing Data

MIIVefa — 0.1.2

Exploratory Factor Analysis Using Model Implied Instrumental Variables

MIIVsem — 0.5.8

Model Implied Instrumental Variable (MIIV) Estimation of Structural Equation Models

mikropml — 1.6.1

User-Friendly R Package for Supervised Machine Learning Pipelines

miLAG — 1.0.2

Calculates Microbial Lag Duration (on the Population Level) from Provided Growth Curve Data

mildsvm — 0.4.0

Multiple-Instance Learning with Support Vector Machines

miLineage — 2.1

Association Tests for Microbial Lineages on a Taxonomic Tree

milorGWAS — 0.7

Mixed Logistic Regression for Genome-Wide Analysis Studies (GWAS)

milr — 0.3.1

Multiple-Instance Logistic Regression with LASSO Penalty

mime — 0.12

Map Filenames to MIME Types

MIMER — 1.0.3

Data Wrangling for Antimicrobial Resistance Studies

mimi — 0.2.0

Main Effects and Interactions in Mixed and Incomplete Data

MiMIR — 1.5

Metabolomics-Based Models for Imputing Risk

mimiSBM — 0.0.1.3

Mixture of Multilayer Integrator Stochastic Block Models

MIMSunit — 0.11.2

Algorithm to Compute Monitor Independent Movement Summary Unit (MIMS-Unit)

mimsy — 0.6.4

Calculate MIMS Dissolved Gas Concentrations Without Getting a Headache

minb — 0.1.0

Multiple-Inflated Negative Binomial Model

mind — 1.1.0

Multivariate Model Based Inference for Domains

MindOnStats — 0.11

Data sets included in Utts and Heckard's Mind on Statistics

mineCitrus — 1.0.0

Extract and Analyze Median Molecule Intensity from 'citrus' Output

mined — 1.0-3

Minimum Energy Designs

MinEDfind — 0.1.3

A Bayesian Design for Minimum Effective Dosing-Finding Trial

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