All packages

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MBESS — 4.9.3

The MBESS R Package

mbest — 0.6

Moment-Based Estimation for Hierarchical Models

MBHdesign — 2.3.15

Spatial Designs for Ecological and Environmental Surveys

mbir — 1.3.5

Magnitude-Based Inferences

mblm — 0.12.1

Median-Based Linear Models

MBmca — 1.0.1-3

Nucleic Acid Melting Curve Analysis

MBMethPred — 0.1.4.2

Medulloblastoma Subgroups Prediction

mbmixture — 0.4

Microbiome Mixture Analysis

MBNMAdose — 0.4.3

Dose-Response MBNMA Models

MBNMAtime — 0.2.4

Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models

mboost — 2.9-10

Model-Based Boosting

mbr — 0.0.1

Mass Balance Reconstruction

mbrdr — 1.1.1

Model-Based Response Dimension Reduction

mbreaks — 1.0.0

Estimation and Inference for Structural Breaks in Linear Regression Models

mbRes — 0.1.7

Exploration of Multiple Biomarker Responses using Effect Size

mbrglm — 0.0.1

Median Bias Reduction in Binomial-Response GLMs

MBSGS — 1.1.0

Multivariate Bayesian Sparse Group Selection with Spike and Slab

MBSP — 4.0

Multivariate Bayesian Model with Shrinkage Priors

mbsts — 3.0

Multivariate Bayesian Structural Time Series

mBvs — 1.92

Bayesian Variable Selection Methods for Multivariate Data

mc.heterogeneity — 0.1.2

A Monte Carlo Based Heterogeneity Test for Meta-Analysis

mc2d — 0.2.1

Tools for Two-Dimensional Monte-Carlo Simulations

MCARtest — 1.2.1

Optimal Nonparametric Testing of Missing Completely at Random

mcauchyd — 1.2.0

Multivariate Cauchy Distribution; Kullback-Leibler Divergence

MCAvariants — 2.6.1

Multiple Correspondence Analysis Variants

mcb — 0.1.15

Model Confidence Bounds

MCBackscattering — 0.1.1

Monte Carlo Simulation for Surface Backscattering

mcbiopi — 1.1.6

Matrix Computation Based Identification of Prime Implicants

mcboost — 0.4.3

Multi-Calibration Boosting

mcca — 0.7.0

Multi-Category Classification Accuracy

mccca — 1.1.0.1

Visualizing Class Specific Heterogeneous Tendencies in Categorical Data

mccf1 — 1.1

Creates the MCC-F1 Curve and Calculates the MCC-F1 Metric and the Best Threshold

mcclust — 1.0.1

Process an MCMC Sample of Clusterings

MCCM — 0.1.0

Mixed Correlation Coefficient Matrix

mccmeiv — 2.1

Analysis of Matched Case Control Data with a Mismeasured Exposure that is Accompanied by Instrumental Variables

mccr — 0.4.4

The Matthews Correlation Coefficient

MCDA — 0.1.0

Support for the Multicriteria Decision Aiding Process

mcemGLM — 1.1.3

Maximum Likelihood Estimation for Generalized Linear Mixed Models

mcen — 1.2.1

Multivariate Cluster Elastic Net

mcga — 3.0.7

Machine Coded Genetic Algorithms for Real-Valued Optimization Problems

mcgf — 1.1.0

Markov Chain Gaussian Fields Simulation and Parameter Estimation

mcgibbsit — 1.2.2

Warnes and Raftery's 'MCGibbsit' MCMC Run Length and Convergence Diagnostic

MChtest — 1.0-3

Monte Carlo Hypothesis Tests with Sequential Stopping

MCI — 1.3.3

Multiplicative Competitive Interaction (MCI) Model

MCID — 0.1.0

Estimating the Minimal Clinically Important Difference

MCL — 1.0

Markov Cluster Algorithm

mclm — 0.2.7

Mastering Corpus Linguistics Methods

mclogit — 0.9.6

Multinomial Logit Models, with or without Random Effects or Overdispersion

mclust — 6.1.1

Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

mclustAddons — 0.8

Addons for the 'mclust' Package

mclustcomp — 0.3.3

Measures for Comparing Clusters

MCM — 0.1.7

Estimating and Testing Intergenerational Social Mobility Effect

mcmc — 0.9-8

Markov Chain Monte Carlo

MCMC.OTU — 1.0.10

Bayesian Analysis of Multivariate Counts Data in DNA Metabarcoding and Ecology

MCMC.qpcr — 1.2.4

Bayesian Analysis of qRT-PCR Data

MCMC4Extremes — 1.1

Posterior Distribution of Extreme Value Models in R

mcmcderive — 0.1.2

Derive MCMC Parameters

mcmcensemble — 3.1.0

Ensemble Sampler for Affine-Invariant MCMC

MCMCglmm — 2.36

MCMC Generalised Linear Mixed Models

mcmcOutput — 0.1.3

Functions to Store, Manipulate and Display Markov Chain Monte Carlo (MCMC) Output

MCMCpack — 1.7-0

Markov Chain Monte Carlo (MCMC) Package

mcmcplots — 0.4.3

Create Plots from MCMC Output

MCMCprecision — 0.4.0

Precision of Discrete Parameters in Transdimensional MCMC

mcmcr — 0.6.1

Manipulate MCMC Samples

mcmcsae — 0.7.7

Markov Chain Monte Carlo Small Area Estimation

mcmcse — 1.5-0

Monte Carlo Standard Errors for MCMC

MCMCtreeR — 1.1

Prepare MCMCtree Analyses and Plot Bayesian Divergence Time Analyses Estimates on Trees

MCMCvis — 0.16.3

Tools to Visualize, Manipulate, and Summarize MCMC Output

mcMST — 1.1.1

A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem

mcmsupply — 1.1.1

Estimating Public and Private Sector Contraceptive Market Supply Shares

mco — 1.16

Multiple Criteria Optimization Algorithms and Related Functions

MCOE — 0.4.0

Creates New Folders and Loads Standard Practices for Monterey County Office of Education

Mcomp — 2.8

Data from the M-Competitions

mcompanion — 0.6

Objects and Methods for Multi-Companion Matrices

mcount — 1.0.0

Marginalized Count Regression Models

mcp — 0.3.4

Regression with Multiple Change Points

MCPAN — 1.1-21

Multiple Comparisons Using Normal Approximation

mcparallelDo — 1.1.0

A Simplified Interface for Running Commands on Parallel Processes

MCPMod — 1.0-10.1

Design and Analysis of Dose-Finding Studies

MCPModBC — 1.1

Improved Inference in Multiple Comparison Procedure – Modelling

MCPModGeneral — 0.1-1

A Supplement to the 'DoseFinding' Package for the General Case

MCPModPack — 0.5

Simulation-Based Design and Analysis of Dose-Finding Trials

mcprofile — 1.0-1

Testing Generalized Linear Hypotheses for Generalized Linear Model Parameters by Profile Deviance

MCPtests — 1.0.1

Multiples Comparisons Procedures

mcr — 1.3.3

Method Comparison Regression

mcradds — 1.1.0

Processing and Analyzing of Diagnostics Trials

mcreplicate — 0.1.2

Multi-Core Replicate

mcrPioda — 1.3.3

Method Comparison Regression - Mcr Fork for M- And MM-Deming Regression

MCS — 0.1.3

Model Confidence Set Procedure

MCSim — 1.0

Determine the Optimal Number of Clusters

mcStats — 0.1.2

Visualize Results of Statistical Hypothesis Tests

mcstatsim — 0.1.0

Monte Carlo Statistical Simulation Tools Using a Functional Approach

mctest — 1.3.1

Multicollinearity Diagnostic Measures

mctq — 0.3.2

Tools to Process the Munich ChronoType Questionnaire (MCTQ)

MCTrend — 1.0.1

Monte Carlo Trend Analysis

mcunit — 0.3.2

Unit Tests for MC Methods

mcvis — 1.0.8

Multi-Collinearity Visualization

mcwr — 1.0.0

Markov Chains with Rewards

md — 1.0.4

Selecting Bandwidth for Kernel Density Estimator with Minimum Distance Method

md.log — 0.2.0

Produces Markdown Log File with a Built-in Function Call

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