Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends ggplot2 for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
Useful functions to analyze proteomic workflows including number of identifications, data completeness, missed cleavages, quantitative and retention time precision etc. Various software outputs are supported such as ProteomeDiscoverer', Spectronaut', DIA-NN and MaxQuant'.
You can use the set of wrappers for analytical schemata to reduce the effort in writing machine-readable data. The set of all-in-one wrappers will cover widely used functions from data analysis packages.
This package provides a wrapper for the OpenTripPlanner <http://www.opentripplanner.org/> REST API. Queries are submitted to the relevant OpenTripPlanner API resource, the response is parsed and useful R objects are returned.
Generates a position balanced or nearly position balanced block design with given parameters. This package can also convert a given proper and equireplicate block design into a position balanced or nearly position balanced block design.
This package provides a function PWI() that calculates prize winner indices based on bibliometric data is provided. The default is the Derek de Solla Price Memorial Medal'. Users can provide recipients of other prizes.
This package provides digital tools for performing analyses within Social Dynamics and complexity in the Ancient Mediterranean (SDAM), which is a research group based at the Department of History and Classical Studies at Aarhus University.
Used to construct the URLs and parameters of Socrata Open Data API <https://dev.socrata.com> calls, using the API's SoQL parameter format. Has method-chained and sensical syntax. Plays well with pipes.
Fits linear regression models on datasets residing in SQL databases without pulling data into R memory. Computes sufficient statistics inside the database engine via a single aggregation query and solves the normal equations in R.
Takea Semantic Structure Analysis (TSSA) and Sakai Sequential Relation Analysis (SSRA) for polytomous items. Package includes functions for generating a sequential relation table and a treegram to visualize the sequential relations between pairs of items.
The main purpose of this package is to propose a rigorous framework to fairly compare trip distribution laws and models as described in Lenormand et al. (2016) <doi:10.1016/j.jtrangeo.2015.12.008>.
Temporal SNA tools for continuous- and discrete-time longitudinal networks having vertex, edge, and attribute dynamics stored in the networkDynamic format. This work was supported by grant R01HD68395 from the National Institute of Health.
Fitting tree-structured varying coefficient models (Berger et al. (2019), <doi:10.1007/s11222-018-9804-8>). Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.
Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 <doi:10.1093/bib/bby095> ).
An implementation of EDM algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with Rcpp wrappers around the cppEDM library. It implements the simplex projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the S-map algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, multiview embedding described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
An implementation of a number of Global Trend models for time series forecasting that are Bayesian generalizations and extensions of some Exponential Smoothing models. The main differences/additions include 1) nonlinear global trend, 2) Student-t error distribution, and 3) a function for the error size, so heteroscedasticity. The methods are particularly useful for short time series. When tested on the well-known M3 dataset, they are able to outperform all classical time series algorithms. The models are fitted with MCMC using the rstan package.
This package provides implementations of a classifier based on the "Classification Based on Associations" (CBA). It can be used for building classification models from association rules. Rules are pruned in the order of precedence given by the sort criteria and a default rule is added. The final classifier labels provided instances. CBA was originally proposed by Liu, B. Hsu, W. and Ma, Y. Integrating Classification and Association Rule Mining. Proceedings KDD-98, New York, 27-31 August. AAAI. pp80-86 (1998, ISBN:1-57735-070-7).
This package helps with the analysis of array CGH data by detecting of the breakpoints in the genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified.
This package contains linear and nonlinear regression methods based on partial least squares and penalization techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.
This package contains:
facilities for working with grouped data:
dosomething to data stratifiedbysome variables.implementations of least-squares means, general linear contrasts, and
miscellaneous other utilities.
The package provides different distances measurements to calculate the difference between genesets. Based on these scores the genesets are clustered and visualized as graph. This is all presented in an interactive Shiny application for easy usage.
Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination.
Retrieve and import data from the INKAR database (Indikatoren und Karten zur Raum- und Stadtentwicklung Datenbank, <https://www.inkar.de>) of the Federal Office for Building and Regional Planning (BBSR) in Bonn using their JSON API.
Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see <https://cvxopt.org> for more information).