All packages

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drifter — 0.2.1

Concept Drift and Concept Shift Detection for Predictive Models

DrillR — 0.1

R Driver for Apache Drill

drimmR — 1.0.1

Estimation, Simulation and Reliability of Drifting Markov Models

DrImpute — 1.0

Imputing Dropout Events in Single-Cell RNA-Sequencing Data

DRIP — 2.3

Discontinuous Regression and Image Processing

driveR — 0.4.1

Prioritizing Cancer Driver Genes Using Genomics Data

droll — 0.1.0

Analyze Roll Distributions

DRomics — 2.6-2

Dose Response for Omics

drone — 1.0.0

Data for Data Visualisation Geometries Encyclopedia

dropout — 2.2.0

Handling Incomplete Responses in Survey Data Analysis

dropR — 1.0.3

Dropout Analysis by Condition

droptest — 0.1.3

Simulates LOX Drop Testing

drord — 1.0.1

Doubly-Robust Estimators for Ordinal Outcomes

drought — 1.2

Statistical Modeling and Assessment of Drought

drpop — 0.0.3

Efficient and Doubly Robust Population Size Estimation

DRquality — 0.2.1

Quality Measurements for Dimensionality Reduction

DRR — 0.0.4

Dimensionality Reduction via Regression

drtmle — 1.1.2

Doubly-Robust Nonparametric Estimation and Inference

drugDemand — 0.1.3

Drug Demand Forecasting

drugdevelopR — 1.0.2

Utility-Based Optimal Phase II/III Drug Development Planning

DrugExposureDiagnostics — 1.1.2

Diagnostics for OMOP Common Data Model Drug Records

drugprepr — 0.0.4

Prepare Electronic Prescription Record Data to Estimate Drug Exposure

drugsens — 0.1.0

Automated Analysis of 'QuPath' Output Data and Metadata Extraction

DrugSim2DR — 0.1.1

Predict Drug Functional Similarity to Drug Repurposing

DrugUtilisation — 1.0.2

Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model

drumr — 0.1.0

Turn R into a Drum Machine

DRviaSPCN — 0.1.5

Drug Repurposing in Cancer via a Subpathway Crosstalk Network

ds — 4.0

Descriptive Statistics

ds4psy — 1.0.0

Data Science for Psychologists

dsa — 1.0.12

Seasonal Adjustment of Daily Time Series

DSAIDE — 0.9.6

Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution)

DSAIRM — 0.9.6

Dynamical Systems Approach to Immune Response Modeling

DSAM — 1.0.2

Data Splitting Algorithms for Model Developments

dsample — 0.91.3.4

Discretization-Based Direct Random Sample Generation

dsb — 2.0.0

Normalize & Denoise Droplet Single Cell Protein Data (CITE-Seq)

DSBayes — 2023.1.0

Bayesian Subgroup Analysis in Clinical Trials

dscore — 1.9.0

D-Score for Child Development

dscoreMSM — 0.1.0

Survival Proximity Score Matching in Multi-State Survival Model

dsdp — 0.1.1

Density Estimation with Semidefinite Programming

dsem — 1.6.0

Dynamic Structural Equation Models

DSI — 1.7.1

'DataSHIELD' Interface

dsims — 1.0.6

Distance Sampling Simulations

DSjobtracker — 2.0.0

What Skills and Qualifications are Required for Data Science Related Jobs?

DSL — 0.1-7

Distributed Storage and List

dslabs — 0.8.0

Data Science Labs

dsld — 0.2.2

Data Science Looks at Discrimination

dslice — 1.2.2

Dynamic Slicing

DSLite — 1.4.0

'DataSHIELD' Implementation on Local Datasets

dsm — 2.3.3

Density Surface Modelling of Distance Sampling Data

dsmisc — 0.3.3

Data Science Box of Pandora Miscellaneous

dsmmR — 1.0.5

Estimation and Simulation of Drifting Semi-Markov Models

DSMolgenisArmadillo — 2.0.9

'DataSHIELD' Client for 'MOLGENIS Armadillo'

dsmSearch — 1.1.1

DSM and LiDAR downloader

DSOpal — 1.4.0

'DataSHIELD' Implementation for 'Opal'

dsos — 0.1.2

Dataset Shift with Outlier Scores

dspline — 1.0.2

Tools for Computations with Discrete Splines

DSpoty — 0.1.0

Get 'Spotify' API Multiple Information

dsrTest — 1.0.0

Tests and Confidence Intervals on Directly Standardized Rates for Several Methods

DSSAT — 0.0.9

A Comprehensive R Interface for the DSSAT Cropping Systems Model

dssd — 1.0.3

Distance Sampling Survey Design

DSSP — 0.1.1

Implementation of the Direct Sampling Spatial Prior

dst — 1.8.0

Using the Theory of Belief Functions

dstabledist — 0.1.0

The Discrete Stable Distribution Functions

DstarM — 0.5.0

Analyze Two Choice Reaction Time Data with the D*M Method

dstat — 1.0.4

Conditional Sensitivity Analysis for Matched Observational Studies

dstat2x2xk — 0.2.0

Demonstrated Insensitivity to Bias in 2x2xK Contingency Tables

dSTEM — 2.0-1

Multiple Testing of Local Extrema for Detection of Change Points

dsTidyverse — 1.0.4

'DataSHIELD' 'Tidyverse' Serverside Package

dsTidyverseClient — 1.0.2

'DataSHIELD' 'Tidyverse' Clientside Package

dSVA — 1.0

Direct Surrogate Variable Analysis

DSWE — 1.8.2

Data Science for Wind Energy

DT — 0.33

A Wrapper of the JavaScript Library 'DataTables'

Dtableone — 1.1.0

Tabular Comparison of Paired Diagnostic Tests

dtangle — 2.0.9

Cell Type Deconvolution from Gene Expressions

DTAplots — 1.0.2.5

Creates Plots Accompanying Bayesian Diagnostic Test Accuracy Meta-Analyses

DTAT — 0.3-7

Dose Titration Algorithm Tuning

DTAXG — 0.1.0

Diagnostic Test Assessment in the Absence of Gold Standard

dTBM — 3.0

Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models

dtComb — 1.0.7

Statistical Combination of Diagnostic Tests

DTComPair — 1.2.6

Comparison of Binary Diagnostic Tests in a Paired Study Design

DtD — 0.2.2

Distance to Default

DTDA — 3.0.1

Doubly Truncated Data Analysis

DTDA.cif — 1.0.2

Doubly Truncated Data Analysis, Cumulative Incidence Functions

DTDA.ni — 1.0.1

Doubly Truncated Data Analysis, Non Iterative

DTEBOP2 — 1.0.3

Bayesian Optimal Phase II Randomized Clinical Trial Design with Delayed Outcomes

dtgiw — 1.0.0

Discrete Transmuted Generalized Inverse Weibull Distribution

dti — 1.5.4.3

Analysis of Diffusion Weighted Imaging (DWI) Data

dtlcor — 0.1.0

Multiplicity Control on Drop-the-Losers Designs

dtmapi — 0.0.2

Fetching Data from the 'Displacement Tracking Matrix'

DTMCPack — 0.1-3

Suite of Functions Related to Discrete-Time Discrete-State Markov Chains

dtp — 0.1.0

Dynamic Panel Threshold Model

dtpcrm — 0.1.1

Dose Transition Pathways for Continual Reassessment Method

dtplyr — 1.3.1

Data Table Back-End for 'dplyr'

dtrackr — 0.4.6

Track your Data Pipelines

dtreg — 1.1.1

Interact with Data Type Registries and Create Machine-Readable Data

DTRKernSmooth — 1.1.0

Estimate and Make Inference About Optimal Treatment Regimes via Smoothed Methods

DTRlearn2 — 1.1

Statistical Learning Methods for Optimizing Dynamic Treatment Regimes

DTRreg — 2.3

DTR Estimation and Inference via G-Estimation, Dynamic WOLS, Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv)

dtrSurv — 1.5

Dynamic Treatment Regimes for Survival Analysis

DTSEA — 0.0.3

Drug Target Set Enrichment Analysis

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