All packages

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datoramar — 0.1.0

Interface to the 'Datorama' API

datos — 0.5.1

Traduce al Español Varios Conjuntos de Datos de Práctica

datplot — 1.1.1

Preparation of Object Dating Ranges for Density Plots (Aoristic Analysis)

datr — 0.1.0

'Dat' Protocol Interface

datrProfile — 0.1.0

Column Profile for Tables and Datasets

dauphin — 0.3.1

Compact Standard for Australian Phone Numbers

Davies — 1.2-0

The Davies Quantile Function

dawai — 1.2.6

Discriminant Analysis with Additional Information

daymetr — 1.7.1

Interface to the 'Daymet' Web Services

daySupply — 0.1.0

Calculating Days' Supply and Daily Dose of Prescriptions

dbacf — 0.2.8

Autocovariance Estimation via Difference-Based Methods

dbarts — 0.9-26

Discrete Bayesian Additive Regression Trees Sampler

dbcsp — 0.0.2.1

Distance-Based Common Spatial Patterns

dbd — 0.0-22

Discretised Beta Distribution

DBEST — 1.8

Detecting Breakpoints and Estimating Segments in Trend

DBfit — 2.0

A Double Bootstrap Method for Analyzing Linear Models with Autoregressive Errors

dbflobr — 0.2.2

Read and Write Files to SQLite Databases

dbGaPCheckup — 1.1.0

dbGaP Checkup

dbglm — 1.0.0

Generalised Linear Models by Subsampling and One-Step Polishing

DBHC — 0.0.3

Sequence Clustering with Discrete-Output HMMs

dbhydroR — 0.2-8

'DBHYDRO' Hydrologic and Water Quality Data

DBI — 1.2.2

R Database Interface

DBItest — 1.8.0

Testing DBI Backends

dblcens — 1.1.9

Compute the NPMLE of Distribution Function from Doubly Censored Data, Plus the Empirical Likelihood Ratio for F(T)

dBlockmodeling — 0.2.3

Deterministic Blockmodeling of Signed, One-Mode and Two-Mode Networks

dblr — 0.1.0

Discrete Boosting Logistic Regression

dbMC — 1.0.0

Confidence Interval for Matrix Completion via De-Biased Estimator

DBModelSelect — 0.2.0

Distribution-Based Model Selection

dbmss — 2.9-0

Distance-Based Measures of Spatial Structures

dbnlearn — 0.1.0

Dynamic Bayesian Network Structure Learning, Parameter Learning and Forecasting

DBNMFrank — 0.1.0

Rank Selection for Non-Negative Matrix Factorization

dbnR — 0.7.8

Dynamic Bayesian Network Learning and Inference

dbparser — 2.0.2

Drugs Databases Parser

dbplot — 0.3.3

Simplifies Plotting Data Inside Databases

dbplyr — 2.5.0

A 'dplyr' Back End for Databases

DBpower — 0.1.0

Finite Sample Power Calculations for Detection Boundary Tests

DBR — 1.4.1

Discrete Beta Regression

dbscan — 1.1-12

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms

dbstats — 2.0.2

Distance-Based Statistics

dbWebForms — 0.1.0

Produce R Functions to Create HTML Forms Based on SQL Meta Data

dbx — 0.3.1

A Fast, Easy-to-Use Database Interface

dc3net — 1.2.0

Inferring Condition-Specific Networks via Differential Network Inference

DCCA — 0.1.1

Detrended Fluctuation and Detrended Cross-Correlation Analysis

DCchoice — 0.2.0

Analyzing Dichotomous Choice Contingent Valuation Data

dccmidas — 0.1.2

DCC Models with GARCH and GARCH-MIDAS Specifications in the Univariate Step, RiskMetrics, Moving Covariance and Scalar and Diagonal BEKK Models

dccpp — 0.1.0

Fast Computation of Distance Correlations

DCEM — 2.0.5

Clustering Big Data using Expectation Maximization Star (EM*) Algorithm

DCEmgmt — 0.0.1

DCE Data Reshaping and Processing

DCEtool — 1.1.0

Efficient and Accessible Discrete Choice Experiments

DCG — 0.9.3

Data Cloud Geometry (DCG): Using Random Walks to Find Community Structure in Social Network Analysis

DChaos — 0.1-7

Chaotic Time Series Analysis

dChipIO — 0.1.5

Methods for Reading dChip Files

dcifer — 1.2.1

Genetic Relatedness Between Polyclonal Infections

DCL — 0.1.2

Claims Reserving under the Double Chain Ladder Model

DCLEAR — 1.0.13

Distance Based Cell Lineage Reconstruction

dclone — 2.3-2

Data Cloning and MCMC Tools for Maximum Likelihood Methods

dclust — 0.1.0

Divisive Hierarchical Clustering

DCluster — 0.2-10

Functions for the Detection of Spatial Clusters of Diseases

DClusterm — 1.0-1

Model-Based Detection of Disease Clusters

dcm2 — 1.0.2

Calculating the M2 Model Fit Statistic for Diagnostic Classification Models

dcmle — 0.4-1

Hierarchical Models Made Easy with Data Cloning

dcmodify — 0.9.0

Modify Data Using Externally Defined Modification Rules

DCODE — 1.0

List Linear n-Peptide Constraints for Overlapping Protein Regions

dcortools — 0.1.6

Providing Fast and Flexible Functions for Distance Correlation Analysis

dcorVS — 1.0

Variable Selection Algorithms Using the Distance Correlation

dcov — 0.1.1

A Fast Implementation of Distance Covariance

dCovTS — 1.4

Distance Covariance and Correlation for Time Series Analysis

DCPO — 0.5.3

Dynamic Comparative Public Opinion

DCSmooth — 1.1.2

Nonparametric Regression and Bandwidth Selection for Spatial Models

dcTensor — 1.2.0

Discrete Matrix/Tensor Decomposition

dCUR — 1.0.1

Dimension Reduction with Dynamic CUR

dcurver — 0.9.2

Utility Functions for Davidian Curves

dcurves — 0.4.0

Decision Curve Analysis for Model Evaluation

ddalpha — 1.3.15

Depth-Based Classification and Calculation of Data Depth

ddc — 1.0.1

Distance Density Clustering Algorithm

DDD — 5.2.2

Diversity-Dependent Diversification

dde — 1.0.5

Solve Delay Differential Equations

DDHFm — 1.1.3

Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays)

ddi — 0.1.0

The Data Defect Index for Samples that May not be IID

ddiv — 0.1.1

Data Driven I-v Feature Extraction

DDIwR — 0.18

DDI with R

DDL — 1.0.2

Doubly Debiased Lasso (DDL)

DDM — 1.0-0

Death Registration Coverage Estimation

ddml — 0.2.0

Double/Debiased Machine Learning

DDoutlier — 0.1.0

Distance & Density-Based Outlier Detection

ddp — 0.0.3

Desirable Dietary Pattern

ddpca — 1.1

Diagonally Dominant Principal Component Analysis

ddpcr — 1.15.2

Analysis and Visualization of Droplet Digital PCR in R and on the Web

ddplot — 0.0.1

Create D3 Based SVG Graphics

DDPM — 0.1.0

Data Sets for Discrete Probability Models

DDPNA — 0.3.3

Disease-Drived Differential Proteins Co-Expression Network Analysis

DDRTree — 0.1.5

Learning Principal Graphs with DDRTree

ddsPLS — 1.2.1

Data-Driven Sparse Partial Least Squares

ddst — 1.4

Data Driven Smooth Tests

ddtlcm — 0.1.1

Latent Class Analysis with Dirichlet Diffusion Tree Process Prior

deadband — 0.1.0

Statistical Deadband Algorithms Comparison

deal — 1.2-42

Learning Bayesian Networks with Mixed Variables

deaR — 1.4.1

Conventional and Fuzzy Data Envelopment Analysis

debar — 0.1.1

A Post-Clustering Denoiser for COI-5P Barcode Data

DEBBI — 0.1.0

Differential Evolution-Based Bayesian Inference

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