All packages

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kml — 2.4.6.1

K-Means for Longitudinal Data

kml3d — 2.4.6.1

K-Means for Joint Longitudinal Data

kmodR — 0.2.0

K-Means with Simultaneous Outlier Detection

KMsurv — 0.1-5

Data sets from Klein and Moeschberger (1997), Survival Analysis

KMunicate — 0.2.4

KMunicate-Style Kaplan–Meier Plots

KnapsackSampling — 0.1.1

Generate Feasible Samples of a Knapsack Problem

KneeArrower — 1.0.0

Finds Cutoff Points on Knee Curves

knitcitations — 1.0.12

Citations for 'Knitr' Markdown Files

knitLatex — 0.9.0

'Knitr' Helpers - Mostly Tables

knitr — 1.45

A General-Purpose Package for Dynamic Report Generation in R

knitrBootstrap — 1.0.3

'knitr' Bootstrap Framework

knitrdata — 0.6.1

Data Language Engine for 'knitr' / 'rmarkdown'

knitrProgressBar — 1.1.0

Provides Progress Bars in 'knitr'

knitxl — 0.1.0

Generates a Spreadsheet Report from an 'rmarkdown' File

knn.covertree — 1.0

An Accurate kNN Implementation with Multiple Distance Measures

knnp — 2.0.0

Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)

KNNShiny — 0.1.0

Interactive Document for Working with KNN Analysis

kNNvs — 0.1.0

k Nearest Neighbors with Grid Search Variable Selection

knnwtsim — 1.0.0

K Nearest Neighbor Forecasting with a Tailored Similarity Metric

knockoff — 0.3.6

The Knockoff Filter for Controlled Variable Selection

KnockoffHybrid — 1.0.0

Hybrid Analysis of Population and Trio Data with Knockoff Statistics for FDR Control

KnockoffScreen — 0.3.0

Whole-Genome Sequencing Data Analysis via Knockoff Statistics

KnockoffTrio — 1.0.2

Trio Data Analysis with Knockoff Statistics for FDR Control

knotR — 1.0-4

Knot Diagrams using Bezier Curves

KnowBR — 2.2

Discriminating Well Surveyed Spatial Units from Exhaustive Biodiversity Databases

kntnr — 0.4.4

R Client for 'kintone' API

KoboconnectR — 1.2.2

Download Data from Kobotoolbox to R

KODAMA — 2.4

Knowledge Discovery by Accuracy Maximization

kofdata — 0.2.1

Get Data from the 'KOF Datenservice' API

kofnGA — 1.3

A Genetic Algorithm for Fixed-Size Subset Selection

KOGMWU — 1.2

Functional Summary and Meta-Analysis of Gene Expression Data

kohonen — 3.0.12

Supervised and Unsupervised Self-Organising Maps

kokudosuuchi — 1.0.0

Utilities for 'Kokudo Suuchi'

komaletter — 0.5.0

Simply Beautiful PDF Letters from Markdown

konfound — 0.5.0

Quantify the Robustness of Causal Inferences

KONPsurv — 1.0.4

KONP Tests: Powerful K-Sample Tests for Right-Censored Data

KOR.addrlink — 1.0.1

Matching Address Data to Reference Index

koRpus — 0.13-8

Text Analysis with Emphasis on POS Tagging, Readability, and Lexical Diversity

koRpus.lang.en — 0.1-4

Language Support for 'koRpus' Package: English

kosel — 0.0.1

Variable Selection by Revisited Knockoffs Procedures

kosis — 0.0.1

Korean Statistical Information Service (KOSIS)

KoulMde — 3.2.1

Koul's Minimum Distance Estimation in Regression and Image Segmentation Problems

Kpart — 1.2.2

Cubic Spline Fitting with Knot Selection

KPC — 0.1.2

Kernel Partial Correlation Coefficient

kpcalg — 1.0.1

Kernel PC Algorithm for Causal Structure Detection

kpeaks — 1.1.0

Determination of K Using Peak Counts of Features for Clustering

kpmt — 0.1.0

Known Population Median Test

kpodclustr — 1.1

Method for Clustering Partially Observed Data

KraljicMatrix — 0.2.1

A Quantified Implementation of the Kraljic Matrix

kriens — 0.1

Continuation Passing Style Development

krige — 0.6.2

Geospatial Kriging with Metropolis Sampling

kriging — 1.2

Ordinary Kriging

KrigInv — 1.4.2

Kriging-Based Inversion for Deterministic and Noisy Computer Experiments

krippendorffsalpha — 2.0

Measuring Agreement Using Krippendorff's Alpha Coefficient

KRIS — 1.1.6

Keen and Reliable Interface Subroutines for Bioinformatic Analysis

KRLS — 1.0-0

Kernel-Based Regularized Least Squares

krm — 2022.10-17

Kernel Based Regression Models

KRMM — 1.0

Kernel Ridge Mixed Model

kronos — 1.0.0

Microbiome Oriented Circadian Rhythm Analysis Toolkit

ks — 1.14.2

Kernel Smoothing

KSA — 0.1.0

Retained Component Criterion for Principal Component Analysis

kSamples — 1.2-10

K-Sample Rank Tests and their Combinations

KScorrect — 1.4.0

Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests

KSD — 1.0.1

Goodness-of-Fit Tests using Kernelized Stein Discrepancy

KSEAapp — 0.99.0

Kinase-Substrate Enrichment Analysis

kselection — 0.2.1

Selection of K in K-Means Clustering

KSgeneral — 1.1.3

Computing P-Values of the K-S Test for (Dis)Continuous Null Distribution

ksharp — 0.1.0.1

Cluster Sharpening

ksNN — 0.1.2

K* Nearest Neighbors Algorithm

KSPM — 0.2.1

Kernel Semi-Parametric Models

ksrlive — 1.0

Identify Kinase Substrate Relationships Using Dynamic Data

kssa — 0.0.1

Known Sub-Sequence Algorithm

kst — 0.5-4

Knowledge Space Theory

kStatistics — 2.1.1

Unbiased Estimators for Cumulant Products and Faa Di Bruno's Formula

kstIO — 0.4-0

Knowledge Space Theory Input/Output

kstMatrix — 0.2-0

Basic Functions in Knowledge Space Theory Using Matrix Representation

ktaucenters — 1.0.0

Robust Clustering Procedures

KTensorGraphs — 1.1

Co-Tucker3 Analysis of Two Sequences of Matrices

ktsolve — 1.3.1

Configurable Function for Solving Families of Nonlinear Equations

ktweedie — 1.0.3

'Tweedie' Compound Poisson Model in the Reproducing Kernel Hilbert Space

kuiper.2samp — 1.0

Two-Sample Kuiper Test

Kurt — 1.1

Performs Kurtosis-Based Statistical Analyses

kutils — 1.73

Project Management Tools

kvh — 1.4.2

Read/Write Files in Key-Value-Hierarchy Format

kyotil — 2024.1-30

Utility Functions for Statistical Analysis Report Generation and Monte Carlo Studies

kza — 4.1.0.1

Kolmogorov-Zurbenko Adaptive Filters

kzs — 1.4

Kolmogorov-Zurbenko Spatial Smoothing and Applications

l0ara — 0.1.6

Sparse Generalized Linear Model with L0 Approximation for Feature Selection

L0Learn — 2.1.0

Fast Algorithms for Best Subset Selection

l1ball — 0.1.0

L1-Ball Prior for Sparse Regression

L1centrality — 0.0.3

Graph/Network Analysis Based on L1 Centrality

l1kdeconv — 1.2.0

Deconvolution for LINCS L1000 Data

L1pack — 0.41-24

Routines for L1 Estimation

l1spectral — 0.99.6

An L1-Version of the Spectral Clustering

l2boost — 1.0.3

Exploring Friedman's Boosting Algorithm for Regularized Linear Regression

L2DensityGoFtest — 0.6.0

Density Goodness-of-Fit Test

L2E — 2.0

Robust Structured Regression via the L2 Criterion

L2hdchange — 1.0

L2 Inference for Change Points in High-Dimensional Time Series

LA — 2.2

Lioness Algorithm (LA)

LabApplStat — 1.4.4

Miscellaneous Scripts from the Data Science Laboratory (UCPH)

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