All packages

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LMfilteR — 0.1.3.1

Filter Methods for Parameter Estimation in Linear and Non Linear Regression Models

lmfor — 1.6

Functions for Forest Biometrics

lmForc — 1.0.0

Linear Model Forecasting

lmhelprs — 0.3.0

Helper Functions for Linear Model Analysis

lmls — 0.1.0

Gaussian Location-Scale Regression

lmm — 1.4

Linear Mixed Models

LMMELSM — 0.2.0

Fit Latent Multivariate Mixed Effects Location Scale Models

lmmot — 0.1.4

Multiple Ordinal Tobit (MOT) Model

lmmpar — 0.1.0

Parallel Linear Mixed Model

LMMsolver — 1.0.8

Linear Mixed Model Solver

LMMstar — 1.1.0

Repeated Measurement Models for Discrete Times

LMN — 1.1.3

Inference for Linear Models with Nuisance Parameters

lmodel2 — 1.7-3

Model II Regression

LMoFit — 0.1.7

Advanced L-Moment Fitting of Distributions

lmom — 3.0

L-Moments

lmomco — 2.5.1

L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions

Lmoments — 1.3-1

L-Moments and Quantile Mixtures

lmomPi — 0.6.6

(Precipitation) Frequency Analysis and Variability with L-Moments from 'lmom'

lmomRFA — 3.6

Regional Frequency Analysis using L-Moments

LMPdata — 0.1.0

Easy Import of the EU Labour Market Policy Data

lmPerm — 2.1.0

Permutation Tests for Linear Models

lmQCM — 0.2.4

An Algorithm for Gene Co-Expression Analysis

lmreg — 1.2

Data and Functions Used in Linear Models and Regression with R: An Integrated Approach

lmridge — 1.2.2

Linear Ridge Regression with Ridge Penalty and Ridge Statistics

lmSubsets — 0.5-2

Exact Variable-Subset Selection in Linear Regression

lmtest — 0.9-40

Testing Linear Regression Models

lmtestrob — 0.1

Outlier Robust Specification Testing

lmtp — 1.4.0

Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies

lmviz — 0.2.0

A Package to Visualize Linear Models Features and Play with Them

lmw — 0.0.2

Linear Model Weights

lncDIFF — 1.0.0

Long Non-Coding RNA Differential Expression Analysis

LncFinder — 1.1.5

LncRNA Identification and Analysis Using Heterologous Features

LncPath — 1.1

Identifying the Pathways Regulated by LncRNA Sets of Interest

LNIRT — 0.5.1

LogNormal Response Time Item Response Theory Models

lnmCluster — 0.3.1

Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data

lnmixsurv — 3.1.6

Bayesian Mixture Log-Normal Survival Model

LNPar — 0.1.0

Estimation and Testing for a Lognormal-Pareto Mixture

loa — 0.2.48.3

Lattice Options and Add-Ins

loadeR — 1.2.0

Load Data for Analysis System

loadings — 0.5.1

Loadings for Principal Component Analysis and Partial Least Squares

loadshaper — 1.1.1

Producing Load Shape with Target Peak and Load Factor

LoBrA — 1.0

Generalized Spline Mixed Effect Models for Longitudinal Breath Data

LobsterCatch — 0.1.0

Models the Capture Processes in American Lobster Trap Fishery

lobstr — 1.1.2

Visualize R Data Structures with Trees

localboot — 0.9.2

Local Bootstrap Methods for Various Networks

LocalControl — 1.1.4

Nonparametric Methods for Generating High Quality Comparative Effectiveness Evidence

LocalCop — 0.0.2

Local Likelihood Inference for Conditional Copula Models

localFDA — 1.0.0

Localization Processes for Functional Data Analysis

localgauss — 0.41

Estimating Local Gaussian Parameters

localICE — 0.1.1

Local Individual Conditional Expectation

localIV — 0.3.1

Estimation of Marginal Treatment Effects using Local Instrumental Variables

localModel — 0.5

LIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles

localScore — 1.0.11

Package for Sequence Analysis by Local Score

localsolver — 2.3

R API to LocalSolver

locaR — 0.1.2

A Set of Tools for Sound Localization

locateip — 0.1.2

Locate IP Addresses with 'ip-api'

locatexec — 0.1.1

Detection and Localization of Executable Files

locationgamer — 0.1.0

Identification of Location Game Equilibria in Networks

LocaTT — 1.1.2

Geographically-Conscious Taxonomic Assignment for Metabarcoding

locfdr — 1.1-8

Computes Local False Discovery Rates

locfit — 1.5-9.10

Local Regression, Likelihood and Density Estimation

locits — 1.7.7

Test of Stationarity and Localized Autocovariance

Lock5Data — 3.0.0

Datasets for "Statistics: UnLocking the Power of Data"

LocKer — 1.1

Locally Sparse Estimator of Generalized Varying Coefficient Model for Asynchronous Longitudinal Data

locpol — 0.8.0

Kernel Local Polynomial Regression

locpolExpectile — 0.1.1

Local Polynomial Expectile Regression

locStra — 1.9

Fast Implementation of (Local) Population Stratification Methods

LOCUS — 1.0

Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity

locuszoomr — 0.3.5

Gene Locus Plot with Gene Annotations

loder — 0.2.1

Dependency-Free Access to PNG Image Files

lodGWAS — 1.0-7

Genome-Wide Association Analysis of a Biomarker Accounting for Limit of Detection

lodi — 0.9.2

Limit of Detection Imputation for Single-Pollutant Models

lodr — 1.0

Linear Model Fitting with LOD Covariates

loedata — 1.0.1

Data Sets from "Lectures on Econometrics" by Chirok Han

loewesadditivity — 0.1.0

Loewe's Additivity

log — 1.1.1

Record Events and Issues

log4r — 0.4.3

A Fast and Lightweight Logging System for R, Based on 'log4j'

LOGAN — 1.0.1

Log File Analysis in International Large-Scale Assessments

logbin — 2.0.5

Relative Risk Regression Using the Log-Binomial Model

LogConcDEAD — 1.6-10

Log-Concave Density Estimation in Arbitrary Dimensions

logconcens — 0.17-3

Maximum Likelihood Estimation of a Log-Concave Density Based on Censored Data

logcondens — 2.1.8

Estimate a Log-Concave Probability Density from Iid Observations

logcondiscr — 1.0.6

Estimate a Log-Concave Probability Mass Function from Discrete i.i.d. Observations

logger — 0.3.0

A Lightweight, Modern and Flexible Logging Utility

logging — 0.10-108

R Logging Package

loggit — 2.1.1

Modern Logging for the R Ecosystem

loggit2 — 2.3.1

Easy-to-Use, Dependencyless Logger

logib — 0.1.2

Salary Analysis by the Swiss Federal Office for Gender Equality

logiBin — 0.3

Binning Variables to Use in Logistic Regression

logicDT — 1.0.4

Identifying Interactions Between Binary Predictors

LogicForest — 2.1.1

Logic Forest

LogicReg — 1.6.6

Logic Regression

logihist — 1.0

Combined Graphs for Logistic Regression

login — 0.9.3

'shiny' Login Module

logistf — 1.26.0

Firth's Bias-Reduced Logistic Regression

logistic4p — 1.6

Logistic Regression with Misclassification in Dependent Variables

LogisticCopula — 0.1.0

A Copula Based Extension of Logistic Regression

LogisticCurveFitting — 0.1.0

Logistic Curve Fitting by Rhodes Method

logisticPCA — 0.2

Binary Dimensionality Reduction

LogisticRCI — 1.1

Linear and Logistic Regression-Based Reliable Change Index

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