- algaeClassify::csrTraitsDatabase of functional traits for MFG classification, derived from Rimet et al. 2019
- algaeClassify::lakegenevaexample dataset from lake Geneva, Switzerland
- algaeClassify::mfgTraitsFunctional Trait Database derived from Rimet et al.
- algaeClassify::mfg_csr_libraryMFG-CSR correspondence based on CSR-trait relationships in Reynolds et al. 1988 and MFG-trait relationships in Salmaso et al. 2015
- algaeClassify::species_mfg_libraryTrait-based MFG classifications for common Eurasion/North American phytoplankton species. See accompanying manuscript for sources
- algaeClassify::traitrangessurface/volume ratio and max linear dimension criteria for CSR From Reynolds 1988 and Reynolds 2006
- bamlss::GolfPrices of Used Cars Data
- bamlss::LondonBoroughsLondon Fire Data
- bamlss::LondonBoundariesLondon Fire Data
- bamlss::LondonFStationsLondon Fire Data
- bamlss::LondonFireLondon Fire Data
- bamlss::TempIbkTemperature data.
- bamlss::fatalitiesWeekly Number of Fatalities in Austria
- bamlss::simdataReference data.
- batchLLM::beliefsBeliefs Dataset
- bayesammi::MaizData for Genotypes by Environment Interaction (GEI)
- baystability::cultivo2008Data for Genotypes by Environment Interaction (GEI)
- baystability::cultivo2009Data for Genotypes by Environment Interaction (GEI)
- BRcal::foreclosureForeclosure Monitoring Predictions data
- BRcal::hockeyHockey Home Team Win Predictions data
- bvhar::etf_vixCBOE ETF Volatility Index Dataset
- bvhar::trading_dayTime points and Financial Events
- calidad::casenEncuesta de Caracterización Socioeconómica Nacional 2020 - CASEN en Pandemia 2020
- calidad::eneEncuesta Nacional de Empleo - ENE. 2020-efm
- calidad::enuscEncuesta Nacional Urbana de Seguridad ciudadana 2019 - ENUSC 2019
- calidad::epf_personasVIII Encuesta de Presupuestos Familiares
- carbonr::airportsTable of airport detail data
- carbonr::example_clinical_theatreClinical Theatre Data
- carbonr::seaportsDataset of different seaports
- carbonr::stationsDataset of UK train stations
- CCAMLRGIS::CCAMLRpCCAMLRGIS Projection
- CCAMLRGIS::CoastSimplified and subsettable coastline
- CCAMLRGIS::Depth_colsBathymetry colors
- CCAMLRGIS::Depth_cols2Bathymetry colors with Fishable Depth range
- CCAMLRGIS::Depth_cutsBathymetry depth classes
- CCAMLRGIS::Depth_cuts2Bathymetry depth classes with Fishable Depth range
- CCAMLRGIS::GridDataExample dataset for create_PolyGrids
- CCAMLRGIS::LabelsPolygon labels
- CCAMLRGIS::LineDataExample dataset for create_Lines
- CCAMLRGIS::PieDataExample dataset for create_Pies
- CCAMLRGIS::PieData2Example dataset for create_Pies
- CCAMLRGIS::PointDataExample dataset for create_Points
- CCAMLRGIS::PolyDataExample dataset for create_Polys
- CDsampling::trauma_dataTrauma data with multinomial response
- CDsampling::trial_dataGenerated clinical trial data with binary response
- CLVTools::apparelDynCovTime-varying Covariates for the Apparel Retailer Dataset
- CLVTools::apparelDynCovFutureFuture Time-varying Covariates for the Apparel Retailer Dataset
- CLVTools::apparelStaticCovTime-invariant Covariates for the Apparel Retailer Dataset
- CLVTools::apparelTransApparel Retailer Dataset
- CLVTools::cdnowCDNOW dataset
- cNORM::CDCBMI growth curves from age 2 to 25
- cNORM::elfeSentence completion test from ELFE 1-6
- cNORM::ppvtVocabulary development from 2.5 to 17
- cocons::holesHoles Data Set
- cocons::holes_bmHoles with trend + multiple realizations Data Set
- cocons::stripesStripes Data Set
- codebook::bfiMock BFI data
- DanielBiostatistics10th::EXA_C01_S04_01Example Data
- DanielBiostatistics10th::EXA_C02_S05_05Example Data
- DanielBiostatistics10th::EXA_C06_S02_04Example Data
- DanielBiostatistics10th::EXA_C07_S02_03Example Data
- DanielBiostatistics10th::EXA_C07_S03_02Example Data
- DanielBiostatistics10th::EXA_C07_S04_01Example Data
- DanielBiostatistics10th::EXA_C07_S07_01Example Data
- DanielBiostatistics10th::EXA_C08_S02_01Example Data
- DanielBiostatistics10th::EXA_C08_S03_01Example Data
- DanielBiostatistics10th::EXA_C08_S04_01Example Data
- DanielBiostatistics10th::EXA_C08_S04_02Example Data
- DanielBiostatistics10th::EXA_C08_S05_02Example Data
- DanielBiostatistics10th::EXA_C09_S03_01Example Data
- DanielBiostatistics10th::EXA_C09_S07_01Example Data
- DanielBiostatistics10th::EXA_C10_S03_01Example Data
- DanielBiostatistics10th::EXA_C10_S06_01Example Data
- DanielBiostatistics10th::EXA_C11_S01_01Example Data
- DanielBiostatistics10th::EXA_C11_S01_02Example Data
- DanielBiostatistics10th::EXA_C11_S02_01Example Data
- DanielBiostatistics10th::EXA_C11_S02_03Example Data
- DanielBiostatistics10th::EXA_C11_S03_01Example Data
- DanielBiostatistics10th::EXA_C11_S04_02Example Data
- DanielBiostatistics10th::EXA_C11_S05_01Example Data
- DanielBiostatistics10th::EXA_C12_S02_03Example Data
- DanielBiostatistics10th::EXA_C13_S03_02Example Data
- DanielBiostatistics10th::EXA_C13_S05_01Example Data
- DanielBiostatistics10th::EXA_C13_S06_01Example Data
- DanielBiostatistics10th::EXA_C13_S07_01Example Data
- DanielBiostatistics10th::EXA_C13_S08_02Example Data
- DanielBiostatistics10th::EXA_C13_S09_01Example Data
- DanielBiostatistics10th::EXA_C13_S09_02Example Data
- DanielBiostatistics10th::EXA_C13_S10_01Example Data
- DanielBiostatistics10th::EXA_C13_S10_02Example Data
- DanielBiostatistics10th::EXA_C14_S03_01Example Data
- DanielBiostatistics10th::EXA_C14_S05_01Example Data
- DanielBiostatistics10th::EXR_C02_S03_01Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_02Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_03Exercise Data
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- DanielBiostatistics10th::EXR_C02_S03_06Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_07Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_08Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_09Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_11Exercise Data
- DanielBiostatistics10th::EXR_C02_S03_12Exercise Data
- DanielBiostatistics10th::EXR_C02_S05_03Exercise Data
- DanielBiostatistics10th::EXR_C02_S05_06Exercise Data
- DanielBiostatistics10th::EXR_C06_S02_05Exercise Data
- DanielBiostatistics10th::EXR_C06_S04_10Exercise Data
- DanielBiostatistics10th::EXR_C06_S09_07Exercise Data
- DanielBiostatistics10th::EXR_C06_S10_07Exercise Data
- DanielBiostatistics10th::EXR_C07_S02_13Exercise Data
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- DanielBiostatistics10th::EXR_C07_S03_03Exercise Data
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- DanielBiostatistics10th::EXR_C07_S03_11Exercise Data
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- DanielBiostatistics10th::EXR_C10_S03_01Exercise Data
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- DanielBiostatistics10th::EXR_C10_S03_03Exercise Data
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- DanielBiostatistics10th::EXR_C10_S03_05Exercise Data
- DanielBiostatistics10th::EXR_C10_S03_06Exercise Data
- DanielBiostatistics10th::EXR_C10_S06_01Exercise Data
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- DanielBiostatistics10th::EXR_C11_S02_01Exercise Data
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- DanielBiostatistics10th::EXR_C11_S03_01Exercise Data
- DanielBiostatistics10th::EXR_C11_S03_02Exercise Data
- DanielBiostatistics10th::EXR_C11_S03_03Exercise Data
- DanielBiostatistics10th::EXR_C11_S04_01Exercise Data
- DanielBiostatistics10th::EXR_C11_S04_02Exercise Data
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- DanielBiostatistics10th::EXR_C11_S05_04Exercise Data
- DanielBiostatistics10th::EXR_C13_S05_01Exercise Data
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- DanielBiostatistics10th::EXR_C13_S06_01Exercise Data
- DanielBiostatistics10th::EXR_C13_S06_02Exercise Data
- DanielBiostatistics10th::EXR_C13_S06_03Exercise Data
- DanielBiostatistics10th::EXR_C13_S07_02Exercise Data
- DanielBiostatistics10th::EXR_C13_S08_01Exercise Data
- DanielBiostatistics10th::EXR_C13_S08_02Exercise Data
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- DanielBiostatistics10th::EXR_C13_S09_01Exercise Data
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- DanielBiostatistics10th::EXR_C13_S09_03Exercise Data
- DanielBiostatistics10th::EXR_C13_S10_01Exercise Data
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- DanielBiostatistics10th::EXR_C13_S10_05Exercise Data
- DanielBiostatistics10th::EXR_C13_S10_06Exercise Data
- DanielBiostatistics10th::EXR_C14_S03_01Exercise Data
- DanielBiostatistics10th::EXR_C14_S03_02Exercise Data
- DanielBiostatistics10th::EXR_C14_S04_03Exercise Data
- DanielBiostatistics10th::LDS_C02_NCBIRTH800Large Data
- DanielBiostatistics10th::LDS_C06_BABYWGTSLarge Data
- DanielBiostatistics10th::LDS_C06_BOYHGTSLarge Data
- DanielBiostatistics10th::LDS_C06_CHOLESTLarge Data
- DanielBiostatistics10th::LDS_C07_HEADCIRCLarge Data
- DanielBiostatistics10th::LDS_C07_HEMOGLOBLarge Data
- DanielBiostatistics10th::LDS_C07_MANDEXTLarge Data
- DanielBiostatistics10th::LDS_C07_PCKDATALarge Data
- DanielBiostatistics10th::LDS_C07_PROTHROMLarge Data
- DanielBiostatistics10th::LDS_C08_CSFDATALarge Data
- DanielBiostatistics10th::LDS_C08_LSADATALarge Data
- DanielBiostatistics10th::LDS_C08_MEDSCORESLarge Data
- DanielBiostatistics10th::LDS_C08_RBCDATALarge Data
- DanielBiostatistics10th::LDS_C08_SACEDATALarge Data
- DanielBiostatistics10th::LDS_C08_SERUMCHOLarge Data
- DanielBiostatistics10th::LDS_C09_CALCIUMLarge Data
- DanielBiostatistics10th::LDS_C09_CEREBRALLarge Data
- DanielBiostatistics10th::LDS_C09_HYPERTENLarge Data
- DanielBiostatistics10th::LDS_C10_LTEXERLarge Data
- DanielBiostatistics10th::LDS_C10_RESPDISLarge Data
- DanielBiostatistics10th::LDS_C10_RISKFACTLarge Data
- DanielBiostatistics10th::LDS_C10_STERLENGTHLarge Data
- DanielBiostatistics10th::LDS_C11_AQUATICSLarge Data
- DanielBiostatistics10th::LDS_C11_TEACHERSLarge Data
- DanielBiostatistics10th::LDS_C11_WGTLOSSLarge Data
- DanielBiostatistics10th::LDS_C12_SMOKINGLarge Data
- DanielBiostatistics10th::LDS_C13_KLETTERLarge Data
- DanielBiostatistics10th::REV_C02_13Review Exercise Data
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- dawai::Vehicle2Vehicle Silhouettes 2
- dendextend::khanMicroarray gene expression dataset from Khan et al., 2001. Subset of 306 genes.
- dendrometeR::dmCDPre-processed dendrometer data from Camp Daniel, Canada
- dendrometeR::dmCDrawRaw dendrometer data from Camp Daniel, Canada
- dendrometeR::dmEDPre-processed dendrometer data from Eldena, Germany
- dendrometeR::dmEDrawRaw dendrometer data from Eldena, Germany
- dendrometeR::dmHSPre-processed dendrometer data from Hinnensee, Germany
- dendrometeR::dmHSrawRaw dendrometer data from Hinnensee, Germany
- dendrometeR::envEDEnvironmental data from Eldena, Germany
- diveMove::divesSample of TDR data from a fur seal
- diveMove::divesTDRSample of TDR data from a fur seal
- diveMove::divesTDRzocSample of TDR data from a fur seal
- diveMove::sealLocsRinged and Gray Seal ARGOS Satellite Location Data
- DRomics::Scenedesmus_apicalConcentration-response effect of triclosan in Scenedesmus vacuolatus
- DRomics::Scenedesmus_metabConcentration-response effect of triclosan in Scenedesmus vacuolatus
- DRomics::Zhou_kidney_pceDose-response kidney transcriptomic effect of Tetrachloroethylene in mouse
- DRomics::zebrafTranscriptomic dose-response to ionizing radiation in zebrafish with batch effect
- dropout::flyingFlying Etiquette Survey Data
- dtComb::allMethodsIncludes machine learning models used for the mlComb function
- dtComb::exampleData1Examples data for the dtComb package
- dtComb::exampleData2A data set containing the carriers of a rare genetic disorder for 120 samples.
- dtComb::exampleData3A simulation data containing 250 diseased and 250 healthy individuals.
- easySimData::dfExample data from 'simdata' package
- EMC2::forstmannForstmann et al.'s data
- EMC2::samples_LNRAn emc object of an LNR model of the Forstmann dataset using the first three subjects
- emmeans::MOatsOats data in multivariate form
- emmeans::auto.noiseAuto Pollution Filter Noise
- emmeans::feedlotFeedlot data
- emmeans::fiberFiber data
- emmeans::neuralgiaNeuralgia data
- emmeans::nutritionNutrition data
- emmeans::orangesSales of oranges
- emmeans::pigsEffects of dietary protein on free plasma leucine concentration in pigs
- emmeans::ubdsUnbalanced dataset
- epichains::covid19_saCOVID-19 Data Repository for South Africa
- equateMultiple::mathTestMath Test Data
- forestplot::HRQoLRegression coefficients and confidence intervals from HRQoL study
- forestplot::dfHRQoLRegression coefficients and confidence intervals from HRQoL study
- ggeffects::coffee_dataSample dataset from a course about analysis of factorial designs
- ggeffects::efcSample dataset from the EUROFAMCARE project
- ggeffects::efc_testSample dataset from the EUROFAMCARE project
- ggeffects::fishSample data set
- ggeffects::lung2Sample data set
- gpbStat::alphaltcLine x Tester data (only Crosses) in Alpha Lattice design.
- gpbStat::alphaltcchkLine x Tester data (Crosses and Checks) in Alpha Lattice
- gpbStat::alphaltcmtLine x Tester data (only Crosses) in Alpha Lattice design.
- gpbStat::alphaltcsLine x Tester data (only Crosses) with single plant observations laid in Alpha Lattice design.
- gpbStat::datdtiData of estimating drought tolerance indices without replication
- gpbStat::datrdtiData of estimating drought tolerance indices with replication
- gpbStat::dm2alphaDiallel Method 2 data in Alpha Lattice.
- gpbStat::dm2rcbdDiallel Method 2 data in RCBD
- gpbStat::rcbdltcLine x Tester data in RCBD
- gpbStat::rcbdltcchkLine x Tester data (Crosses and Checks) in RCBD
- gpbStat::rcbdltcmtLine x Tester data (only Crosses) in Randomized Complete Block design.
- gpbStat::rcbdltcsLine x Tester data (only Crosses) with single plant observations laid in RCBD design.
- GpGp::argo2016Ocean temperatures from Argo profiling floats
- GpGp::jason3Windspeed measurements from Jason-3 Satellite
- GPvam::GPvam.benchmarkBenchmarks of the program using simulated data.
- GPvam::vam_dataSimulated Data
- groc::cookieNear-Infrared (NIR) Spectroscopy of Biscuit Doughs
- groc::prim7prim7 Dataset
- grpnet::autoAuto MPG Data Set
- GSEMA::GeneSetsGSEMA synthetic data
- GSEMA::objectMApathSimGSEMA synthetic data
- GSEMA::study1ExGSEMA synthetic data
- GSEMA::study1PhenoGSEMA synthetic data
- GSEMA::study2ExGSEMA synthetic data
- GSEMA::study2PhenoGSEMA synthetic data
- gss::ColoCanColorectal Cancer Mortality Rate in Indiana Counties
- gss::DiaRetDiabetic Retinopathy
- gss::LakeAcidityWater Acidity in Lakes
- gss::NO2Air Pollution and Road Traffic
- gss::SachsProtein Expression in Human Immune System Cells
- gss::aidsAIDS Incubation
- gss::bacteriuriaTreatment of Bacteriuria
- gss::buffaloBuffalo Annual Snowfall
- gss::climAverage Temperatures During December 1980 Through February 1981
- gss::escEmbryonic Stem Cell from Mouse
- gss::eyetrackEyesight Fixation in Eyetracking Experiments
- gss::gastricGastric Cancer Data
- gss::noxNOx in Engine Exhaust
- gss::ozoneOzone Concentration in Los Angeles Basin
- gss::pennyThickness of US Lincoln Pennies
- gss::stanStanford Heart Transplant Data
- gss::wesdrProgression of Diabetic Retinopathy
- gss::wesdr1Stages of Diabetic Retinopathy
- gtfsio::gtfs_referenceGTFS reference
- hce::ADETEvent-Time dataset for kidney outcomes.
- hce::ADLBLaboratory dataset for Glomerular Filtration Rate (GFR) measurements.
- hce::ADSLBaseline characteristics dataset of patients with kidney function assessments.
- hce::COVID19COVID-19 ordinal scale dataset (full report).
- hce::COVID19bCOVID-19 ordinal scale dataset (preliminary report).
- hce::COVID19plusCOVID-19 ordinal scale dataset for a combination therapy.
- hce::HCE1'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
- hce::HCE2'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
- hce::HCE3'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
- hce::HCE4'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
- hce::KHCEKidney Hierarchical Composite Endpoint dataset.
- HDANOVA::caldanaArabidopsis thaliana growth experiment
- HDANOVA::candiesSensory assessment of candies.
- htetree::simulation.1A Simulated Dataset
- IBMPopSim::EW_popIMD_14England and Wales (EW) 2014 population and death rates by Index of Multiple Deprivation (IMD).
- IBMPopSim::EW_pop_14England and Wales (EW) 2014 population, death and birth rates.
- IBMPopSim::EW_pop_outExample of "human population" after 100 years of simulation.
- IBMPopSim::EWdata_hmdEngland and Wale mortality data (source: Human Mortality Database)
- IBMPopSim::toy_paramsToy parameters for IBMPopSim-human_popIMD vignette example.
- iglu::example_data_1_subjectExample CGM data for one subject with Type II diabetes
- iglu::example_data_5_subjectExample CGM data for 5 subjects with Type II diabetes
- iglu::example_data_hallExample data from Hall et al. (2018)
- iglu::example_meals_hallExample mealtimes data from Hall et al. (2018)
- kbal::lalondeData from National Supported Work program and Panel Study in Income Dynamics
- knfi::col_nameThe Korean and English names of the column names
- knfi::nfi_donghaeNational Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function
- LearnNonparam::Table1.1.1Sodium Contents
- LearnNonparam::Table1.2.1Cycles Until Failure
- LearnNonparam::Table2.1.1Test Scores
- LearnNonparam::Table2.3.1Runoff Minutes
- LearnNonparam::Table2.6.1Hours Until Recharge
- LearnNonparam::Table2.6.2Cerium Amounts
- LearnNonparam::Table2.8.1Ounces Of Beverage
- LearnNonparam::Table3.1.2Normal Samples
- LearnNonparam::Table3.2.2Logarithms of Bacteria Counts
- LearnNonparam::Table3.2.3Saltiness Scores
- LearnNonparam::Table3.3.1Percentages of Clay
- LearnNonparam::Table3.4.1Phosphorus Contents
- LearnNonparam::Table4.1.1Caloric Intake
- LearnNonparam::Table4.1.3Cholesterol Reduction
- LearnNonparam::Table4.4.3Yield Data
- LearnNonparam::Table4.5.3Randomized Complete Block with Ties
- LearnNonparam::Table5.1.2Heterophils and Lymphocytes
- LearnNonparam::Table5.2.2Scores of Projects
- LearnNonparam::Table5.4.2Satisfaction with Pain-Relief Treatment
- lme4breeding::A_exampleBroad sense heritability calculation.
- lme4breeding::A_gryphonGryphon data from the Journal of Animal Ecology
- lme4breeding::A_igeData to fit indirect genetic effects.
- lme4breeding::DT_augmentDT_augment design example.
- lme4breeding::DT_btdataBlue Tit Data for a Quantitative Genetic Experiment
- lme4breeding::DT_cornhybridsCorn crosses and markers
- lme4breeding::DT_cpdataGenotypic and Phenotypic data for a CP population
- lme4breeding::DT_exampleBroad sense heritability calculation.
- lme4breeding::DT_expdesignsData for different experimental designs
- lme4breeding::DT_fulldiallelFull diallel data for corn hybrids
- lme4breeding::DT_gryphonGryphon data from the Journal of Animal Ecology
- lme4breeding::DT_h2Broad sense heritability calculation.
- lme4breeding::DT_halfdiallelhalf diallel data for corn hybrids
- lme4breeding::DT_igeData to fit indirect genetic effects.
- lme4breeding::DT_legendreSimulated data for random regression
- lme4breeding::DT_mohringFull diallel data for corn hybrids
- lme4breeding::DT_polyploidGenotypic and Phenotypic data for a potato polyploid population
- lme4breeding::DT_riceRice lines dataset
- lme4breeding::DT_sleepstudyReaction times in a sleep deprivation study
- lme4breeding::DT_technowGenotypic and Phenotypic data from single cross hybrids (Technow et al.,2014)
- lme4breeding::DT_wheatwheat lines dataset
- lme4breeding::DT_yatesoatsYield of oats in a split-block experiment
- lme4breeding::DTi_cornhybridsCorn crosses and markers
- lme4breeding::GT_cornhybridsCorn crosses and markers
- lme4breeding::GT_cpdataGenotypic and Phenotypic data for a CP population
- lme4breeding::GT_polyploidGenotypic and Phenotypic data for a potato polyploid population
- lme4breeding::GT_riceRice lines dataset
- lme4breeding::GT_wheatwheat lines dataset
- lme4breeding::GTn_riceRice lines dataset
- lme4breeding::MP_cpdataGenotypic and Phenotypic data for a CP population
- lme4breeding::MP_polyploidGenotypic and Phenotypic data for a potato polyploid population
- lme4breeding::Md_technowGenotypic and Phenotypic data from single cross hybrids (Technow et al.,2014)
- lme4breeding::Mf_technowGenotypic and Phenotypic data from single cross hybrids (Technow et al.,2014)
- lme4breeding::P_gryphonGryphon data from the Journal of Animal Ecology
- lmhelprs::data_test1Sample Data: For Testing
- longitudinalData::artificialJointLongData~ Data: artificialJointLongData ~
- longitudinalData::artificialLongData~ Data: artificialLongData ~
- LorenzRegression::Data.IncomesSimulated income data
- LWFBrook90R::slb1_meteoMeteorological Data from the Solling Beech and Spruce experimental site
- LWFBrook90R::slb1_prec2013_hhHourly precipitation data from Solling Beech experimental site 'SLB1' for year 2013
- LWFBrook90R::slb1_soilSoil profile data from the Solling Beech experimental site 'SLB1'
- LWFBrook90R::slb1_standpropAnnual stand properties of the Solling Beech experimental site 'SLB1'
- Matching::GerberGreenImaiGerber and Green Dataset used by Imai
- Matching::lalondeLalonde Dataset
- MDPIexploreR::agricultureArticle data extracted from MDPI journal Agriculture
- MDPIexploreR::horticulturaeArticle data extracted from MDPI journal Horticulturae
- metR::geopotentialGeopotential height
- metR::surfaceSurface height
- metR::temperatureAir temperature
- MixtureMissing::UScostUS Cost of Living Indices in 2019 Data Set
- MixtureMissing::autoAutomobile Data Set
- MixtureMissing::bankruptcyBankruptcy Data Set
- mizer::NS_interactionExample interaction matrix for the North Sea example
- mizer::NS_paramsExample MizerParams object for the North Sea example
- mizer::NS_simExample MizerSim object for the North Sea example
- mizer::NS_species_paramsExample species parameter set based on the North Sea
- mizer::NS_species_params_gearsExample species parameter set based on the North Sea with different gears
- mizer::interAlias for 'NS_interaction'
- mpt::ItalianCitiesCity-Size Paired-Comparison Task
- mpt::MDHennig2020Moral Dilemma Judgment
- mpt::MDreplicationMoral Dilemma Judgment
- mpt::PMSmithBayenProspective Memory and Task Importance
- mpt::PMreplicationProspective Memory and Task Importance
- mpt::ROCBroeder2009Recognition Receiver Operating Characteristics
- mpt::ROCreplicationRecognition Receiver Operating Characteristics
- mpt::WSTKlauer2007Wason Selection Task (WST) and Helpful Hints
- mpt::WSTreplicationWason Selection Task (WST) and Helpful Hints
- mpt::WorldCitiesCity-Size Paired-Comparison Task
- mpt::agememoryAge Differences in Episodic Memory
- mpt::proactRecall Frequencies for DaPolito's Experiment on Proactive Inhibition
- mpt::pwrsim1Simulation-Based Power Analysis for MPT Models
- mpt::pwrsim2Simulation-Based Power Analysis for MPT Models
- mpt::retroactRecall Frequencies in Retroactive Inhibition
- mpt::valenceWorld Valence and Source Memory for Vertical Position
- MultiATSM::BR_jps_outReplications of the JPS (2014) outputs by Bauer and Rudebusch (2017)
- MultiATSM::DomMacroData: Risk Factors for the GVAR - Candelon and Moura (2023)
- MultiATSM::DomesticMacroVarData: Risk Factors - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::FactorsGVARData: Risk Factors for the GVAR - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::GlobalMacroData: Risk Factors - Candelon and Moura (2023)
- MultiATSM::GlobalMacroVarData: Risk Factors - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::ModelParaReplications of the JPS (2014) outputs by the MultiATSM package
- MultiATSM::RiskFactorsData: Risk Factors - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::RiskFactorsData: Risk Factors - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::TradeFlowsData: Trade Flows - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::Trade_FlowsData: Trade Flows - Candelon and Moura (2023)
- MultiATSM::YieldsData: Yields - Candelon and Moura (forthcoming, JFEC)
- MultiATSM::YieldsData: Yields - Candelon and Moura (forthcoming, JFEC)
- multilevLCA::dataIEAData for understanding of good citizenship behaviour
- multilevLCA::dataTOYArtificial data set
- multpois::bs2Between-subjects 2×2 design with dichotomous response
- multpois::bs3Between-subjects 2×2 design with polytomous response
- multpois::icecreamMixed factorial 2×2 design with polytomous response
- multpois::ws2Within-subjects 2×2 design with dichotomous response
- multpois::ws3Within-subjects 2×2 design with polytomous response
- mycaas::AA_knowledge_testExample of a test to showcase the Adaptive Assessment tools
- nda::COVID19_2020Covid'19 case datesets of countries (2020), where the data frame has 138 observations of 18 variables.
- nda::CWTS_2020CWTS Leiden's University Ranking 2020 for all scientific fields, within the period of 2016-2019. 1176 observations (i.e., universities), and 42 variables (i.e., indicators).
- nda::CrimesUSA1990.XCrimes in USA cities in 1990. Independent variables (X)
- nda::CrimesUSA1990.YCrimes in USA cities in 1990. Dependent variable (Y)
- nda::GOVDB2020Governmental and economic data of countries (2020), where the data frame has 138 observations of 2161 variables.
- nda::I40_2020NUTS2 regional development data (2020) of I4.0 readiness, where the data frame has 414 observations of 101 variables.
- neutrostat::citytempTemperature Data of Five Different Cites in Pakistan for July 2022
- neutrostat::dioxinAverage Daily Ingestion of Dioxin in Food Samples with Uncertainities
- neutrostat::goldpriceGold Prices Across Six Indian Cities from February 2022 to January 2023
- NMRphasing::fdatThis is an example data in NMRphasing
- nopaco::scoresHypothetical data of outcomes for two risk models
- NPCox::pbcMayo Clinic Primary Biliary Cholangitis Data
- NSR::nsr_testfileExample NSR data
- packageRank::blog.dataBlog post data.
- packageRank::rstudio.logsEight RStudio Download Logs to Fix Duplicate Logs Errors in 'cranlogs'.
- palaeoverse::GTS2012Geological Timescale 2012
- palaeoverse::GTS2020Geological Timescale 2020
- palaeoverse::interval_keyExample dataset: Interval key for the look_up function
- palaeoverse::reefsExample dataset: Phanerozoic reefs from the PaleoReefs Database
- palaeoverse::tetrapodsExample dataset: Early tetrapod data from the Paleobiology Database
- pedigreemm::mastitisMastitis cases in dairy cattle
- pedigreemm::milkMilk production
- pedigreemm::pedCowsPedigree of the cows in milk
- pedigreemm::pedCowsRPedigree of the cows in milk with 0.70 of the information in pedCows
- pedigreemm::pedSiresPedigree of the sires from mastitis
- phylotypr::trainset9_pdsRDP training set v9
- phylotypr::trainset9_rdpRDP training set v9
- plmmr::admixAdmix: Semi-simulated SNP data
- pln::item5fr5-item Test Data Set
- pln::item9cat59 Item Test Data Set
- pwr4exp::milkAn exemplary dataset of a 4x4 crossover design with 2 squares
- qwraps2::mtcars2mtcars2
- qwraps2::pefrpefr
- qwraps2::spambaseSpambase
- radiant.model::catalogCatalog sales for men's and women's apparel
- radiant.model::direct_marketingDirect marketing data
- radiant.model::dvdData on DVD sales
- radiant.model::housepricesHouseprices
- radiant.model::idealIdeal data for linear regression
- radiant.model::kaggle_upliftKaggle uplift
- radiant.model::ketchupData on ketchup choices
- radiant.model::movie_contractMovie contract decision tree
- radiant.model::ratingsMovie ratings
- rbmi::antidepressant_dataAntidepressant trial data
- Rcompadre::ComadreSubsamples of the COMPADRE Plant Matrix Database and COMADRE Animal Matrix Database for testing and examples
- Rcompadre::CompadreSubsamples of the COMPADRE Plant Matrix Database and COMADRE Animal Matrix Database for testing and examples
- Rcompadre::CompadreLegacySubsample of a legacy version of the COMPADRE Plant Matrix Database for testing and examples
- riverdist::GulkDataset: Gulkana River
- riverdist::Kenai1Dataset: Kenai River 1
- riverdist::Kenai2Dataset: Kenai River 2
- riverdist::Kenai3Dataset: Kenai River 3
- riverdist::KilleyWDataset: Killey River, West Channel
- riverdist::Koyukuk0Dataset: Koyukuk River 0
- riverdist::Koyukuk1Dataset: Koyukuk River 1
- riverdist::Koyukuk2Dataset: Koyukuk River 2
- riverdist::abstreamsDataset: A-B Streams
- riverdist::abstreams0Dataset: A-B Streams 0
- riverdist::fakefishDataset: Fakefish
- riverdist::fakefish_densityDataset: Fakefish Density
- riverdist::line98Dataset: Line 98 of Kenai River 1 (Long-Lat)
- riverdist::smallsetDataset: Smallset
- RWsearch::binarydbCRAN Matrix Of Available Binary Packages (archivedb.rda)
- RWsearch::crandbCRAN Packages (crandb.rda)
- RWsearch::tvdbTask Views (tvdb.rda)
- s2dv::sampleDepthDataSample of Experimental Data for Forecast Verification In Function Of Latitudes And Depths
- s2dv::sampleMapSample Of Observational And Experimental Data For Forecast Verification In Function Of Longitudes And Latitudes
- s2dv::sampleTimeSeriesSample Of Observational And Experimental Data For Forecast Verification As Area Averages
- SCDA::Data2010Spatial dataset to replicate the results for 2010 from Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>
- SCDA::Data2020Spatial dataset to replicate the results for 2020 from Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>)
- SCDA::listWList of 222 spatial weights (style = "W", zero.policy=TRUE) used in Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>)
- seminr::corp_rep_dataMeasurement Instrument for the Corporate Reputation Model
- seminr::corp_rep_data2A Second Measurement Instrument for the Corporate Reputation Model
- seminr::influencer_dataMeasurement Instrument for the Influencer Model
- seminr::mobiMeasurement Instrument for the Mobile Phone Industry
- shapviz::miamiMiami-Dade County House Prices
- simmr::geese_dataGeese stable isotope mixing data set
- simmr::geese_data_day1A smaller version of the Geese stable isotope mixing data set
- simmr::simmr_data_1A simple fake stable isotope mixing data set
- simmr::simmr_data_2A 3-isotope fake stable isotope mixing data set
- simmr::square_dataAn artificial data set used to indicate effect of priors
- SMDIC::envDataenvData
- SMDIC::xCell.dataxCell datasets
- snSMART::data_binaryDataset with binary outcomes
- snSMART::data_doseDose Level dataset with binary outcomes
- snSMART::groupseqDATA_fullGroup sequential full data
- snSMART::groupseqDATA_look1Group sequential data look 1
- snSMART::trialDataMFDataset with continuous outcomes
- SpATS::wheatdataWheat yield in South Australia
- spheredata::CLASSColorado Learning Attitudes about Science Survey (CLASS) dataset
- spheredata::FCIThe Force Concept Inventory (FCI) dataset
- spheredata::FCIkeyThe Force Concept Inventory (FCI) key dataset
- spheredata::FMCEThe Force and Motion Conceptual Evaluation (FMCE) dataset
- spheredata::FMCEkeyThe Force and Motion Conceptual Evaluation (FMCE) key dataset
- spheredata::FMCIThe Fluid Mechanics Concept Inventory (FMCI) dataset
- spheredata::FMCIkeyThe Fluid Mechanics Concept Inventory (FMCI) key dataset
- spheredata::MWCSThe Mechanical Waves Conceptual Survey (MWCS) dataset
- spheredata::MWCSkeyThe Mechanical Waves Conceptual Survey (MWCS) key dataset
- spheredata::RRMCSThe Rotational and Rolling Motion Conceptual Survey (RRMCS) dataset
- spheredata::RRMCSkeyThe Rotational and Rolling Motion Conceptual Survey (RRMCS) key dataset
- spheredata::SAARThe Scientific Abilities Assessment Rubrics (SAAR) dataset
- spheredata::STPFASLThe Survey of Thermodynamic Processes and First and Second Laws (STPFASL) dataset
- spheredata::STPFASLkeyThe Survey of Thermodynamic Processes and First and Second Laws (STPFASL) key dataset
- spheredata::TCEThe Thermal Concept Evaluation (TCE) dataset
- spheredata::TCEkeyThe Thermal Concept Evaluation (TCE) key dataset
- spheredata::demographicStudents' demographic of the SPHERE dataset
- spheredata::literacyStudents' literacy dataset
- spheredata::physicsidentityStudents' physics identity dataset
- spheredata::teachersjudgmentTeachers' judgment dataset
- ssMutPA::Path_ESPath_ES Single-sample mutation-based pathway enrichment score profiles.
- ssMutPA::Path_NamePath_Name
- ssMutPA::RWR_resRWR_res Random walk results based on mutated genes in a single sample.
- ssMutPA::Seeds_ScoreSeeds_Score The local weight of seed nodes.
- ssMutPA::cox_datacox_data Univariate cox proportional hazards regression data.
- ssMutPA::dot_datadot_data A data frame.
- ssMutPA::mut_oncomut_onco A binary mutation matrix.
- ssMutPA::mut_statusmut_status A binary mutation matrix.
- ssMutPA::samp_class_oncosamp_class_onco
- ssMutPA::sample_classsample_class The subtype labels of samples.
- ssMutPA::sur_oncosur_onco
- starter::project_templatesProject templates
- statgenHTP::PhenoarchDat1Greenhouse data for a maize experiment in the PhenoArch platform.
- statgenHTP::PhenovatorDat1Growth chamber data for an Arabidopsis experiment in the Phenovator platform.
- statgenHTP::RootDat1Greenhouse data for an experiment in the RootPhAir platform.
- statgenHTP::noCorrectedRootRoot data corrected for outliers for single observations.
- statgenHTP::spatCorrectedArchMaize data corrected for spatial trends.
- statgenHTP::spatCorrectedVatorArabidopsis data corrected for spatial trends.
- statgenHTP::spatPredArchMaize data, genotypic predictions.
- statgenSTA::TDHeat05Field data for a wheat experiment in Mexico
- statgenSTA::TDMaizeField data for a maize experiment in Tlaltizapan, Mexico
- statgenSTA::dropsRawDROPS data set
- StepReg::creditCardcreditCard
- StepReg::remissionremission
- StepReg::tobaccotobacco
- svyVarSel::simdata_lasso_binomialSimulated complex survey data
- tablexlsx::styleAn R list that contains the styles of each element for formatting data frames in excel files
- tclust::LG5dataLG5data data
- tclust::M5dataM5data data
- tclust::fleaFlea
- tclust::geyser2Old Faithful Geyser Data
- tclust::pinePinus nigra dataset
- tclust::swissbankSwiss banknotes data
- tclust::wholesaleWholesale customers dataset
- tfrmt::data_aeAdverse Events Analysis Results Data
- tfrmt::data_demogDemography Analysis Results Data
- tfrmt::data_efficacyEfficacy Analysis Results Data
- tfrmt::data_labsLabs Analysis Results Data
- tsgarch::dmbpDeutschemark/British pound Exchange Rate
- tsgarch::nikkeiJapanese NIKKEI Stock Index
- winr::respRespiratory dataset
- winr::skinDermatology dataset
- wk::wk_example_wktCreate example geometry objects
- wk::wk_proj_crs_jsonCommon CRS Representations
- wk::wk_proj_crs_viewCommon CRS Representations
- WQM::NWP.rainAustralia NWP rainfall forecasts at lead 1h over Sydney region
- WQM::sampleSample data: Rainfall forecasts data
- xts::sample_matrixSample Data Matrix For xts Example and Unit Testing
