Set of tools aimed at processing meteorological data, converting hourly recorded data to daily, monthly and annual data.

An intuitive, cross-platform graphical data analysis system. It uses menus and dialogs to guide the user efficiently through the data manipulation and analysis process, and has an excel like spreadsheet for easy data frame visualization and editing. Deducer works best when used with the Java based R GUI JGR, but the dialogs can be called from the command line. Dialogs have also been integrated into the Windows Rgui.

Weighted frequency and contingency tables of categorical variables and of the comparison of the mean value of a numerical variable by the levels of a factor, and methods to produce xtable objects of the tables and to plot them. There are also functions to facilitate the character encoding conversion of objects, to quickly convert fixed width files into csv ones, and to export a data.frame to a text file with the necessary R and SPSS codes to reread the data.

Discrete splines are a class of univariate piecewise polynomial functions which are analogous to splines, but whose smoothness is defined via divided differences rather than derivatives. Tools for efficient computations relating to discrete splines are provided here. These tools include discrete differentiation and integration, various matrix computations with discrete derivative or discrete spline bases matrices, and interpolation within discrete spline spaces. These techniques are described in Tibshirani (2020) <doi:10.48550/arXiv.2003.03886>.

Efficient covariate-adjusted estimators of quantities that are useful for establishing the effects of treatments on ordinal outcomes.

The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.

This package implements maximum likelihood and bootstrap methods based on the diversity-dependent birth-death process to test whether speciation or extinction are diversity-dependent, under various models including various types of key innovations. See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, <DOI:10.1098/rspb.2011.1439>, Etienne & Haegeman 2012, Am. Nat. 180: E75-E89, <DOI:10.1086/667574>, Etienne et al. 2016. Meth. Ecol. Evol. 7: 1092-1099, <DOI:10.1111/2041-210X.12565> and Laudanno et al. 2021. Syst. Biol. 70: 389â 407, <DOI:10.1093/sysbio/syaa048>. Also contains functions to simulate the diversity-dependent process.

This package contains Data frames and functions used in the book "Design and Analysis of Experiments with R", Lawson(2015) ISBN-13:978-1-4398-6813-3.

This package provides tools to identify, quantify, analyze, and visualize growth suppression events in tree rings that are often produced by insect defoliation. Described in Guiterman et al. (2020) <doi:10.1016/j.dendro.2020.125750>.

Transform newswire and earnings call transcripts as PDF obtained from Nexis Uni to R data frames. Various newswires and FairDisclosure earnings call formats are supported. Further, users can apply several pre-defined dictionaries on the data based on Graffin et al. (2016)<doi:10.5465/amj.2013.0288> and Gamache et al. (2015)<doi:10.5465/amj.2013.0377>.

In-line functions for multivariate optimization via desirability functions (Derringer and Suich, 1980, <doi:10.1080/00224065.1980.11980968>) with easy use within dplyr pipelines.

Builds both ROC (Receiver Operating Characteristic) and DET (Detection Error Tradeoff) curves from a set of predictors, which are the results of a binary classification system. The curves give a general vision of the performance of the classifier, and are useful for comparing performance of different systems.

Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR), and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data, childhood mortality probabilities and rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR), Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR), and adult mortality indicators such as the Age Specific Mortality Rate (ASMR), Age Adjusted Mortality Rate (AAMR), Age Specific Maternal Mortality Rate (ASMMR), Age Adjusted Maternal Mortality Rate (AAMMR), Age Specific Pregnancy Related Mortality Rate (ASPRMR), Age Adjusted Pregnancy Related Mortality Rate (AAPRMR), Maternal Mortality Ratio (MMR) and Pregnancy Related Mortality Ratio (PRMR). In addition to the indicators, the DHS.rates package estimates sampling errors indicators such as Standard Error (SE), Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI). The package is developed according to the DHS methodology of calculating the fertility indicators and the childhood mortality rates outlined in the "Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, <https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>) and the DHS methodology of estimating the sampling errors indicators outlined in the "DHS Sampling and Household Listing Manual" (ICF International 2012, <https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).

With bivariate data, it is possible to calculate 2-dimensional kernel density estimates that return polygons at given levels of probability. densityarea returns these polygons for analysis, including for calculating their area.

This package contains functions that check for formatting of the Subject Phenotype data set and data dictionary as specified by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.

This package provides a set of functions and a class to connect, extract and upload information from the LSEG Datastream database. This package uses the DSWS API and server used by the Datastream DFO addin'. Details of this API are available at <https://www.lseg.com/en/data-analytics>. Please report issues at <https://github.com/CharlesCara/DatastreamDSWS2R/issues>.

This package provides functionality for users who are learning R or the techniques of data analysis. Written as a collection of wrapper functions, the DTwrapper package facilitates many core operations of data processing. This is achieved with relatively few requirements about the order of the processing steps or knowledge of specialized syntax. DTwrappers creates coding results along with translations to data.table's code. This enables users to benefit from the speed and efficiency of data.table's calculations. Furthermore, the package also provides the translated code for educational purposes so that users can review working examples of coding syntax and calculations.

Offers meta programming style tools to generate configurable R functions that produce HTML forms based on table input and SQL meta data. Also generates functions for collecting the parameters of those HTML forms after they are submitted. Useful for quickly generating HTML forms based on existing SQL tables. To use the resultant functions, the output files containing those functions must be read into the R environment (perhaps using base::source()).

The DALY Calculator is a free, open-source Graphical User Interface (GUI) for stochastic disability-adjusted life year (DALY) calculation.

Simultaneously detect the number and locations of change points in piecewise linear models under stationary Gaussian noise allowing autocorrelated random noise. The core idea is to transform the problem of detecting change points into the detection of local extrema (local maxima and local minima)through kernel smoothing and differentiation of the data sequence, see Cheng et al. (2020) <doi:10.1214/20-EJS1751>. A low-computational and fast algorithm call dSTEM is introduced to detect change points based on the STEM algorithm in D. Cheng and A. Schwartzman (2017) <doi:10.1214/16-AOS1458>.

This package provides a collection of functions to search and download Digital Surface Model (DSM) and Light Detection and Ranging (LiDAR) data via APIs, including OpenTopography <https://portal.opentopography.org/apidocs/> and TNMAccess <https://apps.nationalmap.gov/tnmaccess/#/>, and canopy tree height data.

Several tests for differential methylation in methylation array data, including one-sided differential mean and variance test. Methods used in the package refer to Dai, J, Wang, X, Chen, H and others (2021) "Incorporating increased variability in discovering cancer methylation markers", Biostatistics, submitted.

Set of functions for Data Envelopment Analysis, including classical, fuzzy, cross-efficiency, bootstrapping, and Malmquist 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>.

This package provides a convenient API interface to access immunological data within the CAVD DataSpace'(<https://dataspace.cavd.org>), a data sharing and discovery tool that facilitates exploration of HIV immunological data from pre-clinical and clinical HIV vaccine studies.