All packages

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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 — 0.7.9

Dynamic Bayesian Network Learning and Inference

dbparser — 2.0.3

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 — 1.2-0

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

dbstats — 2.0.2

Distance-Based Statistics

DBTC — 0.1.0

Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis

DBTCShiny — 0.1.2

Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis 'shiny' Application

dbw — 1.1.4

Doubly Robust Distribution Balancing Weighting Estimation

dbWebForms — 0.1.0

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

dbx — 0.3.2

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 — 1.3.0

Discrete Matrix/Tensor Decomposition

dCUR — 1.0.1

Dimension Reduction with Dynamic CUR

dcurver — 0.9.2

Utility Functions for Davidian Curves

dcurves — 0.5.0

Decision Curve Analysis for Model Evaluation

ddalpha — 1.3.16

Depth-Based Classification and Calculation of Data Depth

ddc — 1.0.1

Distance Density Clustering Algorithm

DDD — 5.2.2

Diversity-Dependent Diversification

dde — 1.0.7

Solve Delay Differential Equations

ddecompose — 1.0.0

Detailed Distributional Decomposition

DDHFm — 1.1.4

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 — 0.3.0

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 — 0.2.1

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

debest — 0.1.0

Duration Estimation for Biomarker Enrichment Studies and Trials

DebiasInfer — 0.2

Efficient Inference on High-Dimensional Linear Model with Missing Outcomes

deBif — 0.1.8

Bifurcation Analysis of Ordinary Differential Equation Systems

deBInfer — 0.4.4

Bayesian Inference for Differential Equations

debkeepr — 0.1.1

Analysis of Non-Decimal Currencies and Double-Entry Bookkeeping

DeBoinR — 1.0

Box-Plots and Outlier Detection for Probability Density Functions

debugme — 1.2.0

Debug R Packages

debugr — 0.0.1

Debug Tool to Watch Objects/Expressions While Running an R Script

DeCAFS — 3.3.3

Detecting Changes in Autocorrelated and Fluctuating Signals

DECIDE — 1.3

DEComposition of Indirect and Direct Effects

decido — 0.3.0

Bindings for 'Mapbox' Ear Cutting Triangulation Library

decision — 0.1.0

Statistical Decision Analysis

decisionSupport — 1.114

Quantitative Support of Decision Making under Uncertainty

deckgl — 0.3.0

An R Interface to 'deck.gl'

declared — 0.25

Functions for Declared Missing Values

DeclareDesign — 1.0.10

Declare and Diagnose Research Designs

decode — 1.2

Differential Co-Expression and Differential Expression Analysis

decoder — 1.2.2

Decode Coded Variables to Plain Text and the Other Way Around

decompDL — 0.1.0

Decomposition Based Deep Learning Models for Time Series Forecasting

decomposedPSF — 0.2

Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD)

DecomposeR — 1.0.6

Empirical Mode Decomposition for Cyclostratigraphy

decompr — 6.4.0

Global Value Chain Decomposition

deconvolveR — 1.2-1

Empirical Bayes Estimation Strategies

decor — 1.0.2

Retrieve Code Decorations

DecorateR — 0.1.2

Fit and Deploy DECORATE Trees

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