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r-dbemplikegof
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public |
Goodness-of-fit and two sample comparison tests using sample entropy
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2025-04-22 |
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r-davies
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public |
Various utilities for the Davies distribution.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-dataverse
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public |
Provides access to Dataverse version 4 APIs <https://dataverse.org/>, enabling data search, retrieval, and deposit. For Dataverse versions <= 4.0, use the deprecated 'dvn' package <https://cran.r-project.org/package=dvn>.
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2025-04-22 |
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r-dataseries
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public |
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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-dataqualityr
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The package performs variable level data quality checks including missing values, unique values, frequency tables, and generates summary statistics
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2025-04-22 |
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r-datamaps
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public |
Easily create interactive choropleth maps then add bubbles and arcs by coordinates or region name. These maps can be used directly from the console, from 'RStudio', in 'Shiny' apps and 'R Markdown' documents. 'Shiny' proxies allow to interactively add arcs and bubbles, change choropleth values, or change labels.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-databaseconnectorjars
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public |
Provides external JAR dependencies for the 'DatabaseConnector' package.
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2025-04-22 |
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r-dasst
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public |
Provides methods for reading, displaying, processing and writing files originally arranged for the 'DSSAT-CSM' fixed width format. The 'DSSAT-CSM' cropping system model is described at J.W. Jones, G. Hoogenboomb, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, J.T. Ritchie (2003) <doi:10.1016/S1161-0301(02)00107-7>.
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2025-04-22 |
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r-dashboard
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public |
The dashboard package allows users to create web pages which display interactive data visualizations working in a standard modern browser. It displays them locally using the Rook server. Nor knowledge about web technologies nor Internet connection are required. D3.js is a JavaScript library for manipulating documents based on data. D3 helps the dashboard package bring data to life using HTML, SVG and CSS.
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2025-04-22 |
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r-dark
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public |
The recovery of visual sensitivity in a dark environment is known as dark adaptation. In a clinical or research setting the recovery is typically measured after a dazzling flash of light and can be described by the Mahroo, Lamb and Pugh (MLP) model of dark adaptation. The functions in this package take dark adaptation data and use nonlinear regression to find the parameters of the model that 'best' describe the data. They do this by firstly, generating rapid initial objective estimates of data adaptation parameters, then a multi-start algorithm is used to reduce the possibility of a local minimum. There is also a bootstrap method to calculate parameter confidence intervals. The functions rely upon a 'dark' list or object. This object is created as the first step in the workflow and parts of the object are updated as it is processed.
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2025-04-22 |
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r-dapr
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public |
An easy-to-use, dependency-free set of functions for iterating over elements of various input objects. Functions are wrappers around base apply()/lapply()/vapply() functions but designed to have similar functionality to the mapping functions in the 'purrr' package <https://purrr.tidyverse.org/>. Specifically, function names more explicitly communicate the expected class of the output and functions also allow for the convenient shortcut of '~ .x' instead of the more verbose 'function(.x) .x'.
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2025-04-22 |
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r-dang
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A collection of utility functions.
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2025-04-22 |
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r-dams
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public |
The single largest source of dams in the United States is the National Inventory of Dams (NID) <http://nid.usace.army.mil> from the US Army Corps of Engineers. Entire data from the NID cannot be obtained all at once and NID's website limits extraction of more than a couple of thousand records at a time. Moreover, selected data from the NID's user interface cannot not be saved to a file. In order to make the analysis of this data easier, all the data from NID was extracted manually. Subsequently, the raw data was checked for potential errors and cleaned. This package provides sample cleaned data from the NID and provides functionality to access the entire cleaned NID data.
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2025-04-22 |
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r-dam
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A collection of functions which aim to assist common computational workflow for analysis of matabolomic data..
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2025-04-22 |
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r-dalex2
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public |
Machine Learning models are widely used and have various applications in classification or regression tasks. Due to increasing computational power, availability of new data sources and new methods, ML models are more and more complex. Models created with techniques like boosting, bagging of neural networks are true black boxes. It is hard to trace the link between input variables and model outcomes. They are used because of high performance, but lack of interpretability is one of their weakest sides. In many applications we need to know, understand or prove how input variables are used in the model and what impact do they have on final model prediction. DALEX2 is a collection of tools that help to understand how complex predictive models are working. DALEX2 is a part of DrWhy universe for tools for Explanation, Exploration and Visualisation for Predictive Models.
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2025-04-22 |
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r-daime
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Reverse and model the effects of changing deposition rates on geological data and rates. Based on Hohmann (2018) <doi:10.13140/RG.2.2.23372.51841> .
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2025-04-22 |
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r-dagr
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public |
Functions to draw, manipulate, evaluate directed acyclic graphs and simulate corresponding data.
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2025-04-22 |
