All packages

· A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z ·

mpwR — 0.1.5

Standardized Comparison of Workflows in Mass Spectrometry-Based Bottom-Up Proteomics

MQMF — 0.1.5

Modelling and Quantitative Methods in Fisheries

Mqrcm — 1.3

M-Quantile Regression Coefficients Modeling

mr.pivw — 0.1.1

Penalized Inverse-Variance Weighted Estimator for Mendelian Randomization

mr.raps — 0.2

Two Sample Mendelian Randomization using Robust Adjusted Profile Score

MR.RGM — 0.0.3

Multivariate Bidirectional Mendelian Randomization Networks

mra — 2.16.11

Mark-Recapture Analysis

mratios — 1.4.2

Ratios of Coefficients in the General Linear Model

mrbayes — 0.5.2

Bayesian Summary Data Models for Mendelian Randomization Studies

mrbin — 1.7.5

Metabolomics Data Analysis Functions

mrbsizeR — 1.3

Scale Space Multiresolution Analysis of Random Signals

mRc — 0.1.0

Multi-Visit Closed Population Mark-Recapture Estimates

MRCE — 2.4

Multivariate Regression with Covariance Estimation

mrct — 0.0.1.0

Outlier Detection of Functional Data Based on the Minimum Regularized Covariance Trace Estimator

mrds — 2.3.0

Mark-Recapture Distance Sampling

mreg — 1.2.1

Fits Regression Models When the Outcome is Partially Missing

mregions2 — 1.1.1

Access Data from Marineregions.org: Gazetteer & Data Products

mrf — 0.1.6

Multiresolution Forecasting

mrf2d — 1.0

Markov Random Field Models for Image Analysis

MRFA — 0.6

Fitting and Predicting Large-Scale Nonlinear Regression Problems using Multi-Resolution Functional ANOVA (MRFA) Approach

MRFcov — 1.0.39

Markov Random Fields with Additional Covariates

mrfDepth — 1.0.17

Depth Measures in Multivariate, Regression and Functional Settings

mrfse — 0.4.1

Markov Random Field Structure Estimator

MRG — 0.2.14

Create Non-Confidential Multi-Resolution Grids

mrgsim.parallel — 0.2.1

Simulate with 'mrgsolve' in Parallel

mrgsim.sa — 0.2.0

Sensitivity Analysis with 'mrgsolve'

mrgsolve — 1.5.1

Simulate from ODE-Based Models

MRHawkes — 1.0

Multivariate Renewal Hawkes Process

mri — 1.0.1

Modified Rand and Wallace Indices

mritc — 0.5-3

MRI Tissue Classification

MRMCaov — 0.3.0

Multi-Reader Multi-Case Analysis of Variance

MRMCsamplesize — 1.0.0

Sample Size Estimations for Planning Multi-Reader Multi-Case (MRMC) Studies Without Pilot Data

MRmediation — 1.0.1

A Causal Mediation Method with Methylated Region (MR) as the Mediator

mrMLM — 5.0.1

Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for GWAS

mrMLM.GUI — 4.0.2

Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for Genome-Wide Association Study with Graphical User Interface

mRMRe — 2.1.2.1

Parallelized Minimum Redundancy, Maximum Relevance (mRMR)

mro — 0.1.1

Multiple Correlation

MRPC — 3.1.0

PC Algorithm with the Principle of Mendelian Randomization

mRpostman — 1.1.4

An IMAP Client for R

MRQoL — 1.0

Minimal Clinically Important Difference and Response Shift Effect for Health-Related Quality of Life

MRReg — 0.1.5

MDL Multiresolution Linear Regression Framework

mrregression — 1.0.0

Regression Analysis for Very Large Data Sets via Merge and Reduce

MRS — 1.2.6

Multi-Resolution Scanning for Cross-Sample Differences

MRTAnalysis — 0.1.2

Primary and Secondary Analyses for Micro-Randomized Trials

MRTSampleSize — 0.3.0

A Sample Size Calculator for Micro-Randomized Trials

MRTSampleSizeBinary — 0.1.2

Sample Size Calculator for MRT with Binary Outcomes

MRZero — 0.2.0

Diet Mendelian Randomization

msae — 0.1.5

Multivariate Fay Herriot Models for Small Area Estimation

msaeHB — 0.1.0

Multivariate Small Area Estimation using Hierarchical Bayesian Method

msaenet — 3.1.2

Multi-Step Adaptive Estimation Methods for Sparse Regressions

msaFACE — 0.1.0

Moving Subset Analysis FACE

msamp — 1.0.0

Estimate Sample Size to Detect Bacterial Contamination in a Product Lot

msaR — 0.6.0

Multiple Sequence Alignment for R Shiny

MSbox — 1.4.8

Mass Spectrometry Tools

msBP — 1.4-1

Multiscale Bernstein Polynomials for Densities

MSBStatsData — 0.0.2

Data Sets for Courses at the Münster School of Business

msce — 1.0.1

Hazard of Multi-Stage Clonal Expansion Models

mschart — 0.4.0

Chart Generation for 'Microsoft Word' and 'Microsoft PowerPoint' Documents

MSclassifR — 0.3.3

Automated Classification of Mass Spectra

MSclust — 1.0.4

Multiple-Scaled Clustering

MSCMT — 1.4.0

Multivariate Synthetic Control Method Using Time Series

MScombine — 1.4

Combine Data from Positive and Negative Ionization Mode Finding Common Entities

mscp — 1.0

Multiscale Change Point Detection via Gradual Bandwidth Adjustment in Moving Sum Processes

MSCquartets — 2.0.1

Analyzing Gene Tree Quartets under the Multi-Species Coalescent

MSCsimtester — 1.0.0

Tests of Multispecies Coalescent Gene Tree Simulator Output

mscstexta4r — 0.1.2

R Client for the Microsoft Cognitive Services Text Analytics REST API

mscstts — 0.6.3

R Client for the Microsoft Cognitive Services 'Text-to-Speech' REST API

mscsweblm4r — 0.1.2

R Client for the Microsoft Cognitive Services Web Language Model REST API

msd — 0.3.1

Method of Successive Dichotomizations

msde — 1.0.5

Bayesian Inference for Multivariate Stochastic Differential Equations

msdrought — 0.1.0

Seasonal Mid-Summer Drought Characteristics

mseapca — 2.0.3

Metabolite Set Enrichment Analysis for Loadings

msentropy — 0.1.4

Spectral Entropy for Mass Spectrometry Data

MSEtool — 3.7.1

Management Strategy Evaluation Toolkit

MSG — 0.8

Data and Functions for the Book Modern Statistical Graphics

MSGARCH — 2.51

Markov-Switching GARCH Models

MSGARCHelm — 0.1.0

Hybridization of MS-GARCH and ELM Model

msgpackR — 1.1

A library to serialize or unserialize data in MessagePack format

msgps — 1.3.5

Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net

msgr — 1.1.2

Extends Messages, Warnings and Errors by Adding Levels and Log Files

mshap — 0.1.0

Multiplicative SHAP Values for Two-Part Models

msig — 1.0

An R Package for Exploring Molecular Signatures Database

msigdbr — 7.5.1

MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format

MSigSeg — 0.2.0

Multiple SIGnal SEGmentation

mSigTools — 1.0.7

Mutational Signature Analysis Tools

mSimCC — 0.0.3

Micro Simulation Model for Cervical Cancer Prevention

MSIMST — 1.1

Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood

MSinference — 0.2.1

Multiscale Inference for Nonparametric Time Trend(s)

MSiP — 1.3.7

'MassSpectrometry' Interaction Prediction

msir — 1.3.3

Model-Based Sliced Inverse Regression

mskcc.oncotree — 0.1.1

Interface to the 'OncoTree' API

msltrend — 1.0

Improved Techniques to Estimate Trend, Velocity and Acceleration from Sea Level Records

msm — 1.8

Multi-State Markov and Hidden Markov Models in Continuous Time

msma — 3.1

Multiblock Sparse Multivariable Analysis

msme — 0.5.3

Functions and Datasets for "Methods of Statistical Model Estimation"

MSmix — 1.0.2

Finite Mixtures of Mallows Models with Spearman Distance for Full and Partial Rankings

MSML — 1.0.0.1

Model Selection Based on Machine Learning (ML)

msmtools — 2.0.1

Building Augmented Data to Run Multi-State Models with 'msm' Package

MSMwRA — 1.5

Multivariate Statistical Methods with R Applications

msos — 1.2.0

Data Sets and Functions Used in Multivariate Statistics: Old School by John Marden

Next page