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r-deepgmm
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public |
Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) <doi:10.1007/s11222-017-9793-z> provide a generalization of classical Gaussian mixtures to multiple layers. Each layer contains a set of latent variables that follow a mixture of Gaussian distributions. To avoid overparameterized solutions, dimension reduction is applied at each layer by way of factor models.
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2024-01-16 |
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r-deconvolver
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public |
Empirical Bayes methods for learning prior distributions from data. An unknown prior distribution (g) has yielded (unobservable) parameters, each of which produces a data point from a parametric exponential family (f). The goal is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical Bayes methods. Details and examples are in the paper by Narasimhan and Efron (2020, <doi:10.18637/jss.v094.i11>).
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2024-01-16 |
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r-decoder
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public |
Main function "decode" is used to decode coded key values to plain text. Function "code" can be used to code plain text to code if there is a 1:1 relation between the two. The concept relies on 'keyvalue' objects used for translation. There are several 'keyvalue' objects included in the areas of geographical regional codes, administrative health care unit codes, diagnosis codes and more. It is also easy to extend the use by arbitrary code sets.
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2024-01-16 |
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r-dear
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public |
Set of functions for Data Envelopment Analysis. It runs both classic and fuzzy DEA models. See: Banker, R.; Charnes, A.; Cooper, W.W. (1984). <doi:10.1287/mnsc.30.9.1078>, Charnes, A.; Cooper, W.W.; Rhodes, E. (1978). <doi:10.1016/0377-2217(78)90138-8> and Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). <doi:10.1287/mnsc.27.6.668>.
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2024-01-16 |
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r-decode
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public |
Integrated differential expression (DE) and differential co-expression (DC) analysis on gene expression data based on DECODE (DifferEntial CO-expression and Differential Expression) algorithm.
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2024-01-16 |
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r-dcurves
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public |
Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes, but often require collection of additional information may be cumbersome to apply to models that yield a continuous result. Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. See the following references for details on the methods: Vickers (2006) <doi:10.1177/0272989X06295361>, Vickers (2008) <doi:10.1186/1472-6947-8-53>, and Pfeiffer (2020) <doi:10.1002/bimj.201800240>.
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2024-01-16 |
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r-decision
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public |
Contains a function called dmur() which accepts four parameters like possible values, probabilities of the values, selling cost and preparation cost. The dmur() function generates various numeric decision parameters like MEMV (Maximum (optimum) expected monitory value), best choice, EPPI (Expected profit with perfect information), EVPI (Expected value of the perfect information), EOL (Expected opportunity loss), which facilitate effective decision-making.
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2024-01-16 |
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r-decide
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public |
Calculates various estimates for measures of educational differentials, the relative importance of primary and secondary effects in the creation of such differentials and compares the estimates obtained from two datasets.
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2024-01-16 |
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r-debugr
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public |
Tool to print out the value of R objects/expressions while running an R script. Outputs can be made dependent on user-defined conditions/criteria. Debug messages only appear when a global option for debugging is set. This way, 'debugr' code can even remain in the debugged code for later use without any negative effects during normal runtime.
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2024-01-16 |
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r-debugme
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public |
Specify debug messages as special string constants, and control debugging of packages via environment variables.
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2024-01-16 |
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r-dbplot
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public |
Leverages 'dplyr' to process the calculations of a plot inside a database. This package provides helper functions that abstract the work at three levels: outputs a 'ggplot', outputs the calculations, outputs the formula needed to calculate bins.
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2024-01-16 |
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r-deadband
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public |
Statistical deadband algorithms are based on the Send-On-Delta concept as in Miskowicz(2006,<doi:10.3390/s6010049>). A collection of functions compare effectiveness and fidelity of sampled signals using statistical deadband algorithms.
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2024-01-16 |
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r-ddm
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public |
A set of three two-census methods to the estimate the degree of death registration coverage for a population. Implemented methods include the Generalized Growth Balance method (GGB), the Synthetic Extinct Generation method (SEG), and a hybrid of the two, GGB-SEG. Each method offers automatic estimation, but users may also specify exact parameters or use a graphical interface to guess parameters in the traditional way if desired.
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2024-01-16 |
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r-dbitest
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public |
A helper that tests DBI back ends for conformity to the interface.
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2024-01-16 |
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r-dcovts
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public |
Computing and plotting the distance covariance and correlation function of a univariate or a multivariate time series. Both versions of biased and unbiased estimators of distance covariance and correlation are provided. Test statistics for testing pairwise independence are also implemented. Some data sets are also included. References include: a) Edelmann Dominic, Fokianos Konstantinos and Pitsillou Maria (2019). 'An Updated Literature Review of Distance Correlation and Its Applications to Time Series'. International Statistical Review, 87(2): 237--262. <doi:10.1111/insr.12294>. b) Fokianos Konstantinos and Pitsillou Maria (2018). 'Testing independence for multivariate time series via the auto-distance correlation matrix'. Biometrika, 105(2): 337--352. <doi:10.1093/biomet/asx082>. c) Fokianos Konstantinos and Pitsillou Maria (2017). 'Consistent testing for pairwise dependence in time series'. Technometrics, 59(2): 262--270. <doi:10.1080/00401706.2016.1156024>. d) Pitsillou Maria and Fokianos Konstantinos (2016). 'dCovTS: Distance Covariance/Correlation for Time Series'. R Journal, 8(2):324-340. <doi:10.32614/RJ-2016-049>.
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2024-01-16 |
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r-dchipio
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public |
Functions for reading DCP and CDF.bin files generated by the dChip software.
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2024-01-16 |
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r-dcl
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public |
Statistical modelling and forecasting in claims reserving in non-life insurance under the Double Chain Ladder framework by Martinez-Miranda, Nielsen and Verrall (2012).
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2024-01-16 |
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r-dcg
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public |
Data cloud geometry (DCG) applies random walks in finding community structures for social networks. Fushing, VanderWaal, McCowan, & Koehl (2013) (<doi:10.1371/journal.pone.0056259>).
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2024-01-16 |
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r-dbx
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public |
Provides select, insert, update, upsert, and delete database operations. Supports 'PostgreSQL', 'MySQL', 'SQLite', and more, and plays nicely with the 'DBI' package.
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2024-01-16 |
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r-dbstats
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public |
Prediction methods where explanatory information is coded as a matrix of distances between individuals. Distances can either be directly input as a distances matrix, a squared distances matrix, an inner-products matrix or computed from observed predictors.
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2024-01-16 |
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r-daymetr
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public |
Programmatic interface to the 'Daymet' web services (<http://daymet.ornl.gov>). Allows for easy downloads of 'Daymet' climate data directly to your R workspace or your computer. Routines for both single pixel data downloads and gridded (netCDF) data are provided.
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2024-01-16 |
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r-dbplyr
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public |
A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.
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2024-01-16 |
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r-datos
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Provee una versión traducida de los siguientes conjuntos de datos: 'airlines', 'airports', 'AwardsManagers', 'babynames', 'Batting', 'credit_data', 'diamonds', 'faithful', 'fueleconomy', 'Fielding', 'flights', 'gapminder', 'gss_cat', 'iris', 'Managers', 'mpg', 'mtcars', 'atmos', 'palmerpenguins', 'People, 'Pitching', 'planes', 'presidential', 'table1', 'table2', 'table3', 'table4a', 'table4b', 'table5', 'vehicles', 'weather', 'who'. English: It provides a Spanish translated version of the datasets listed above.
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2024-01-16 |
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r-dbi
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A database interface definition for communication between R and relational database management systems. All classes in this package are virtual and need to be extended by the various R/DBMS implementations.
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2024-01-16 |
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r-daterangepicker
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public |
A Shiny Input for date-ranges, which pops up two calendars for selecting dates, times, or predefined ranges like "Last 30 Days". It wraps the JavaScript library 'daterangepicker' which is available at <https://www.daterangepicker.com>.
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2024-01-16 |
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r-dbhydror
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Client for programmatic access to the South Florida Water Management District's 'DBHYDRO' database at <https://www.sfwmd.gov/science-data/dbhydro>, with functions for accessing hydrologic and water quality data.
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2024-01-16 |
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r-dbest
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A program for analyzing vegetation time series, with two algorithms: 1) change detection algorithm that detects trend changes, determines their type (abrupt or non-abrupt), and estimates their timing, magnitude, number, and direction; 2) generalization algorithm that simplifies the temporal trend into main features. The user can set the number of major breakpoints or magnitude of greatest changes of interest for detection, and can control the generalization process by setting an additional parameter of generalization-percentage.
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2024-01-16 |
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r-davies
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Various utilities for the Davies distribution.
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2024-01-16 |
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r-datasets.load
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public |
Graphical interface for loading datasets in RStudio from all installed (including unloaded) packages, also includes command line interfaces.
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2024-01-16 |
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r-datr
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public |
Interface with the 'Dat' p2p network protocol <https://datproject.org>. Clone archives from the network, share your own files, and install packages from the network.
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2024-01-16 |
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r-datawizard
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public |
A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.
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2024-01-16 |
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r-datetimeutils
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public |
Utilities for handling dates and times, such as selecting particular days of the week or month, formatting timestamps as required by RSS feeds, or converting timestamp representations of other software (such as 'MATLAB' and 'Excel') to R. The package is lightweight (no dependencies, pure R implementations) and relies only on R's standard classes to represent dates and times ('Date' and 'POSIXt'); it aims to provide efficient implementations, through vectorisation and the use of R's native numeric representations of timestamps where possible.
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2024-01-16 |
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r-datetime
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public |
Provides methods for working with nominal dates, times, and durations. Base R has sophisticated facilities for handling time, but these can give unexpected results if, for example, timezone is not handled properly. This package provides a more casual approach to support cases which do not require rigorous treatment. It systematically deconstructs the concepts origin and timezone, and de-emphasizes the display of seconds. It also converts among nominal durations such as seconds, hours, days, and weeks. See '?datetime' and '?duration' for examples. Adapted from 'metrumrg' <http://r-forge.r-project.org/R/?group_id=1215>.
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2024-01-16 |
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r-dataset
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public |
The aim of the 'dataset' package is to make tidy datasets easier to release, exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, well-described, interoperable datasets into release and reuse ready form. A subjective interpretation of the W3C DataSet recommendation and the datacube model <https://www.w3.org/TR/vocab-data-cube/>, which is also used in the global Statistical Data and Metadata eXchange standards, the application of the connected Dublin Core <https://www.dublincore.org/specifications/dublin-core/dcmi-terms/> and DataCite <https://support.datacite.org/docs/datacite-metadata-schema-44/> standards preferred by European open science repositories to improve the findability, accessibility, interoperability and reusability of the datasets.
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2024-01-16 |
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r-dataretrieval
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public |
Collection of functions to help retrieve U.S. Geological Survey and U.S. Environmental Protection Agency water quality and hydrology data from web services. Data are discovered from National Water Information System <https://waterservices.usgs.gov/> and <https://waterdata.usgs.gov/nwis>. Water quality data are obtained from the Water Quality Portal <https://www.waterqualitydata.us/>.
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2024-01-16 |
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r-dataverse
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public |
Provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5), enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0, use the archived 'dvn' package <https://cran.r-project.org/package=dvn>.
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2024-01-16 |
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r-datapreparation
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public |
Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
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2024-01-16 |
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r-dataseries
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Download and import time series from <http://www.dataseries.org>, a comprehensive and up-to-date collection of open data from Switzerland.
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2024-01-16 |
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r-datarobot
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public |
For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.
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2024-01-16 |
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r-datasaurus
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public |
The Datasaurus Dozen is a set of datasets with the same summary statistics. They retain the same summary statistics despite having radically different distributions. The datasets represent a larger and quirkier object lesson that is typically taught via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet contains four very different distributions with the same summary statistics and as such highlights the value of visualisation in understanding data, over and above summary statistics. As well as being an engaging variant on the Quartet, the data is generated in a novel way. The simulated annealing process used to derive datasets from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing" <doi:10.1145/3025453.3025912>.
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2024-01-16 |
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r-datarium
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public |
Contains data organized by topics: categorical data, regression model, means comparisons, independent and repeated measures ANOVA, mixed ANOVA and ANCOVA.
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2024-01-16 |
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r-datapasta
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public |
RStudio addins and R functions that make copy-pasting vectors and tables to text painless.
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2024-01-16 |
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r-datamods
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public |
'Shiny' modules to import data into an application or 'addin' from various sources, and to manipulate them after that.
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2024-01-16 |
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r-datamaid
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public |
Data screening is an important first step of any statistical analysis. dataMaid auto generates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.
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2024-01-16 |
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r-dataeditr
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public |
An interactive editor built on 'rhandsontable' to allow the interactive viewing, entering, filtering and editing of data in R <https://dillonhammill.github.io/DataEditR/>.
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2024-01-16 |
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r-dataexplorer
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public |
Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights. The package scans and analyzes each variable, and visualizes them with typical graphical techniques. Common data processing methods are also available to treat and format data.
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2024-01-16 |
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r-dataframes2xls
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public |
Writes data frames to xls files. It supports multiple sheets and basic formatting.
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2024-01-16 |
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r-datacombine
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public |
Tools for combining and cleaning data sets, particularly with grouped and time series data.
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2024-01-16 |
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r-databaseconnector
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public |
An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', and 'SQLite'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or other 'DBI' drivers to connect to databases.
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2024-01-16 |
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r-dataclean
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public |
Includes functions that researchers or practitioners may use to clean raw data, transferring html, xlsx, txt data file into other formats. And it also can be used to manipulate text variables, extract numeric variables from text variables and other variable cleaning processes. It is originated from a author's project which focuses on creative performance in online education environment. The resulting paper of that study will be published soon.
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2024-01-16 |
