Makes it easy to push data to Power BI using R and the Power BI REST APIs (see <https://docs.microsoft.com/en-us/rest/api/power-bi/>). A set of functions for turning data frames into Power BI datasets and refreshing these datasets are provided. Administrative tasks such as monitoring refresh statuses and pulling metadata about workspaces and users are also supported.

Most of the time floating point arithmetic does approximately the right thing. When adding sums or having products of numbers that greatly differ in magnitude, the floating point arithmetic may be incorrect. This package implements the Kahan (1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum <doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from NumPy', See Castaldo (2008) <doi:10.1137/070679946> for a discussion of accuracy), and arbitrary precision sum (adapted from the fsum in Python ; Shewchuk (1997) <https://people.eecs.berkeley.edu/~jrs/papers/robustr.pdf>). In addition, products are changed to long double precision for accuracy, or changed into a log-sum for accuracy.

This package provides a graphical user interface for viewing and designing various types of graphs of the data. The graphs can be saved in different formats of an image.

Given k populations (can be in thousands), what is the probability that a given subset of size t contains the true top t populations? This package finds this probability and offers three tuning parameters (G, d, L) to relax the definition.

Allows to download current and historical METAR weather reports extract and parse basic parameters and present main weather information. Current reports are downloaded from Aviation Weather Center <https://aviationweather.gov/data/metar/> and historical reports from Iowa Environmental Mesonet web page of Iowa State University ASOS-AWOS-METAR <http://mesonet.agron.iastate.edu/AWOS/>.

This package provides functions to make board game graphics with the ggplot2', grid', rayrender', rayvertex', and rgl packages. Specializes in game diagrams, animations, and "Print & Play" layouts for the piecepack <https://www.ludism.org/ppwiki> but can make graphics for other board game systems. Includes configurations for several public domain game systems such as checkers, (double-18) dominoes, go, piecepack', playing cards, etc.

POM-aSPU test evaluates an association between an ordinal response and multiple phenotypes, for details see Kim and Pan (2017) <DOI:10.1002/gepi.22033>.

This takes in a series of multi-layer raster files and returns a phenology projection raster, following methodologies described in John (2016) <https://etda.libraries.psu.edu/catalog/13521clj5135>.

This package provides functions to get prediction intervals and prediction points of future observations from any continuous distribution.

Extracts growth, survival, and local neighborhood density information from repeated, fine-scale maps of organism occurrence. Further information about this package can be found in our journal article, "plantTracker: An R package to translate maps of plant occurrence into demographic data" published in 2022 in Methods in Ecology and Evolution (Stears, et al., 2022) <doi:10.1111/2041-210X.13950>.

This package provides a broad-view perspective on data via linear mapping of data onto a radial coordinate system. The package contains functions to visualize the residual values of linear regression and Cartesian data in the defined radial scheme. See the pacviz documentation page for more information: <https://pacviz.sriley.dev/>.

Computation of robust standard errors of Poisson fixed effects models, following Wooldridge (1999).

Analysis and measurement of promotion effectiveness on a given target variable (e.g. daily sales). After converting promotion schedule into dummy or smoothed predictor variables, the package estimates the effects of these variables controlled for trend/periodicity/structural change using prophet by Taylor and Letham (2017) <doi:10.7287/peerj.preprints.3190v2> and some prespecified variables (e.g. start of a month).

Identifies the entries with patterned responses for psychometric scales. The patterns included in the package are identical (a, a, a), ascending (a, b, c), descending (c, b, a), alternative (a, b, a, b / a, b, c, a, b, c).

Read R package news files, regardless of whether or not the package is installed.

Statistical power simulation for testing the Rasch Model based on a three-way analysis of variance design with mixed classification.

Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents. Supported by grant NSF DMS 1712839.

Attempts to clean optical character recognition (OCR) errors in legacy Scottish Post Office Directories. Further attempts to match records from trades and general directories.

This package provides convenience functions and pre-programmed Stan models related to the paired comparison factor model. Its purpose is to make fitting paired comparison data using Stan easy. This package is described in Pritikin (2020) <doi:10.1016/j.heliyon.2020.e04821>.

This package provides functions to estimate the kinship matrix of individuals from a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized FST (Wright's fixation index). Method described in Ochoa and Storey (2021) <doi:10.1371/journal.pgen.1009241>.

Pool dilution is a isotope tracer technique wherein a biogeochemical pool is artifically enriched with its heavy isotopologue and the gross productive and consumptive fluxes of that pool are quantified by the change in pool size and isotopic composition over time. This package calculates gross production and consumption rates from closed-system isotopic pool dilution time series data. Pool size concentrations and heavy isotope (e.g., 15N) content are measured over time and the model optimizes production rate (P) and the first order rate constant (k) by minimizing error in the model-predicted total pool size, as well as the isotopic signature. The model optimizes rates by weighting information against the signal:noise ratio of concentration and heavy- isotope signatures using measurement precision as well as the magnitude of change over time. The calculations used here are based on von Fischer and Hedin (2002) <doi:10.1029/2001GB001448> with some modifications.

Using the R package reticulate', this package creates an interface to the pysd toolset. The package provides an R interface to a number of pysd functions, and can read files in Vensim mdl format, and xmile format. The resulting simulations are returned as a tibble', and from that the results can be processed using dplyr and ggplot2'. The package has been tested using python3'.

An implementation of the van Westendorp Price Sensitivity Meter in R, which is a survey-based approach to analyze consumer price preferences and sensitivity (van Westendorp 1976, isbn:9789283100386).

Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. pathfindR is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. pathfindR also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in pathfindR are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR': An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.