All packages

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LipinskiFilters — 1.0.1

Computes and Visualize Lipinski's Parameters

liqueueR — 0.0.1

Implements Queue, PriorityQueue and Stack Classes

lira — 2.0.1

LInear Regression in Astronomy

lisa — 0.1.2

Color Palettes from Color Lisa

lisrelToR — 0.3

Import Output from LISREL into R

list — 9.2.6

Statistical Methods for the Item Count Technique and List Experiment

listArray — 0.1.1

Incomplete Array with Arbitrary R Objects as Indices

listarrays — 0.4.0

A Toolbox for Working with R Arrays in a Functional Programming Style

listcomp — 0.4.1

List Comprehensions

listcompr — 0.4.0

List Comprehension for R

listdown — 0.5.7

Create R Markdown from Lists

listenv — 0.9.1

Environments Behaving (Almost) as Lists

LIStest — 2.1

Tests of independence based on the Longest Increasing Subsequence

listr — 0.1.0

Tools for Lists

listviewer — 4.0.0

'htmlwidget' for Interactive Views of R Lists

listWithDefaults — 1.2.0

List with Defaults

lit — 1.0.0

Latent Interaction Testing for Genome-Wide Studies

lite — 1.1.1

Likelihood-Based Inference for Time Series Extremes

litedown — 0.4

A Lightweight Version of R Markdown

liteq — 1.1.0

Lightweight Portable Message Queue Using 'SQLite'

literanger — 0.1.1

Random Forests for Multiple Imputation Based on 'ranger'

litRiddle — 1.0.0

Dataset and Tools to Research the Riddle of Literary Quality

litteR — 1.0.0

Litter Analysis

litterfitter — 0.1.3

Fit a Collection of Curves to Single Cohort Decomposition Data

littler — 0.3.20

R at the Command-Line via 'r'

liureg — 1.1.2

Liu Regression with Liu Biasing Parameters and Statistics

live — 1.5.13

Local Interpretable (Model-Agnostic) Visual Explanations

liver — 1.18

"Eating the Liver of Data Science"

ljr — 1.4-0

Logistic Joinpoint Regression

LKT — 1.7.0

Logistic Knowledge Tracing

llama — 0.10.1

Leveraging Learning to Automatically Manage Algorithms

llbayesireg — 1.0.0

The L-Logistic Bayesian Regression

LLIC — 3.0.0

Likelihood Criterion (LIC) Analysis for Laplace Regression Model

LLM — 1.1.0

Logit Leaf Model Classifier for Binary Classification

LLMR — 0.1.1

Interface for Large Language Model APIs in R

llogistic — 1.0.3

The L-Logistic Distribution

LLSR — 0.0.3.1

Data Analysis of Liquid-Liquid Systems using R

lm.beta — 1.7-2

Add Standardized Regression Coefficients to Linear-Model-Objects

lm.br — 2.9.8

Linear Model with Breakpoint

lmap — 0.1.3

Logistic Mapping

lmboot — 0.0.1

Bootstrap in Linear Models

LMD — 1.0.0

A Self-Adaptive Approach for Demodulating Multi-Component Signal

lmDiallel — 1.0.1

Linear Fixed/Mixed Effects Models for Diallel Crosses

lmds — 0.1.0

Landmark Multi-Dimensional Scaling

lme4 — 1.1-35.5

Linear Mixed-Effects Models using 'Eigen' and S4

lme4breeding — 1.0.40

Relationship-Based Mixed-Effects Models

lmeInfo — 0.3.2

Information Matrices for 'lmeStruct' and 'glsStruct' Objects

LMERConvenienceFunctions — 3.0

Model Selection and Post-Hoc Analysis for (G)LMER Models

lmeresampler — 0.2.4

Bootstrap Methods for Nested Linear Mixed-Effects Models

lmerPerm — 0.1.9

Perform Permutation Test on General Linear and Mixed Linear Regression

lmerTest — 3.1-3

Tests in Linear Mixed Effects Models

lmeSplines — 1.1-12

Add Smoothing Spline Modelling Capability to `nlme`

LMest — 3.2.4

Generalized Latent Markov Models

lmf — 1.2.1

Functions for Estimation and Inference of Selection in Age-Structured Populations

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 — 0.4.0

Helper Functions for Linear Model Analysis

lmls — 0.1.1

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 — 1.7-4

Model II Regression

LMoFit — 0.1.7

Advanced L-Moment Fitting of Distributions

lmom — 3.2

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 — 3.8

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 — 1.1.6

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 — 0.3.1.1

Lattice Options and Add-Ins

loadeR — 1.3.0

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

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