All packages

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matrixdist — 1.1.9

Statistics for Matrix Distributions

MatrixEQTL — 2.3

Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix Operations

MatrixExtra — 0.1.15

Extra Methods for Sparse Matrices

MatrixHMM — 1.0.0

Parsimonious Families of Hidden Markov Models for Matrix-Variate Longitudinal Data

matrixLaplacian — 1.0

Normalized Laplacian Matrix and Laplacian Map

MatrixLDA — 0.2

Penalized Matrix-Normal Linear Discriminant Analysis

MatrixMixtures — 1.0.0

Model-Based Clustering via Matrix-Variate Mixture Models

MatrixModels — 0.5-3

Modelling with Sparse and Dense Matrices

matrixmodp — 0.2.0

Working with Matrices over Finite Prime Fields

matrixNormal — 0.1.1

The Matrix Normal Distribution

matrixProfile — 0.5.0

Matrix Profile

matrixprofiler — 0.1.9

Matrix Profile for R

matrixsampling — 2.0.0

Simulations of Matrix Variate Distributions

matrixset — 0.3.0

Creating, Manipulating and Annotating Matrix Ensemble

matrixStats — 1.4.1

Functions that Apply to Rows and Columns of Matrices (and to Vectors)

matrixStrucTest — 1.0.0

Tests of Matrix Structure for Construct Validation

matrixTests — 0.2.3

Fast Statistical Hypothesis Tests on Rows and Columns of Matrices

matsbyname — 0.6.10

An Implementation of Matrix Mathematics that Respects Row and Column Names

matsindf — 0.4.8

Matrices in Data Frames

MatSkew — 0.1.5

Matrix Skew-T Parameter Estimation

matuR — 0.0.1.0

Athlete Maturation and Biobanding

mau — 0.1.2

Decision Models with Multi Attribute Utility Theory

mauricer — 2.5.4

Work with 'BEAST2' Packages

MAVE — 1.3.11

Methods for Dimension Reduction

maxaltall — 0.1.0

'FASTA' ML and ‘altall’ Sequences from IQ-TREE .state Files

maxcombo — 1.0

The Group Sequential Max-Combo Test for Comparing Survival Curves

maxent.ot — 1.0.0

Perform Phonological Analyses using Maximum Entropy Optimality Theory

MaxentVariableSelection — 1.0-3

Selecting the Best Set of Relevant Environmental Variables along with the Optimal Regularization Multiplier for Maxent Niche Modeling

maximin — 1.0-5

Space-Filling Design under Maximin Distance

MaximinInfer — 2.0.0

Inference for Maximin Effects in High-Dimensional Settings

maxLik — 1.5-2.1

Maximum Likelihood Estimation and Related Tools

maxlike — 0.1-11

Model Species Distributions by Estimating the Probability of Occurrence Using Presence-Only Data

maxmatching — 0.1.0

Maximum Matching for General Weighted Graph

MaxMC — 0.1.2

Maximized Monte Carlo

maxnet — 0.1.4

Fitting 'Maxent' Species Distribution Models with 'glmnet'

MaxPro — 4.1-2

Maximum Projection Designs

MaxSkew — 1.1

Orthogonal Data Projections with Maximal Skewness

maxstablePCA — 0.1.1

Apply a PCA Like Procedure Suited for Multivariate Extreme Value Distributions

maxstat — 0.7-25

Maximally Selected Rank Statistics

maybe — 1.1.0

The Maybe Monad

MazamaCoreUtils — 0.5.2

Utility Functions for Production R Code

MazamaLocationUtils — 0.4.4

Manage Spatial Metadata for Known Locations

MazamaRollUtils — 0.1.3

Efficient Rolling Functions

MazamaSpatialPlots — 0.2.0

Thematic Plots for Mazama Spatial Datasets

MazamaSpatialUtils — 0.8.7

Spatial Data Download and Utility Functions

MazamaTimeSeries — 0.3.0

Core Functionality for Environmental Time Series

MAZE — 0.0.2

Mediation Analysis for Zero-Inflated Mediators

mazealls — 0.2.0

Generate Recursive Mazes

mazeGen — 0.1.3

Elithorn Maze Generator

mazeinda — 0.0.2

Monotonic Association on Zero-Inflated Data

mazing — 1.0.5

Utilities for Making and Plotting Mazes

MB — 0.1.1

The Use of Marginal Distributions in Conditional Forecasting

MBA — 0.1-2

Multilevel B-Spline Approximation

MBAnalysis — 2.0.2

Multiblock Exploratory and Predictive Data Analysis

mbbe — 0.1.0

Model Based Bio-Equivalence

mbbefd — 0.8.12

Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and Destruction Rate Modelling

MBBEFDLite — 0.0.4

Statistical Functions for the Maxwell-Boltzmann-Bose-Einstein-Fermi-Dirac (MBBEFD) Family of Distributions

MBC — 0.10-6

Multivariate Bias Correction of Climate Model Outputs

MBCbook — 0.1.2

Companion Package for the Book "Model-Based Clustering and Classification for Data Science"

mbend — 1.3.1

Matrix Bending

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 — 2.9-11

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 — 1.2.2

Optimal Nonparametric Testing of Missing Completely at Random

mcauchyd — 1.3.2

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

mcbette — 1.15.3

Model Comparison Using 'babette'

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

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