Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).

PAM (Partitioning Around Medoids) algorithm application to samples of single cell sequencing techniques with a high number of cells (as many as the computer memory allows). The package uses a binary format to store matrices (either full, sparse or symmetric) in files written in the disk that can contain any data type (not just double) which allows its manipulation when memory is sufficient to load them as int or float, but not as double. The PAM implementation is done in parallel, using several/all the cores of the machine, if it has them. This package shares a great part of its code with packages jmatrix and parallelpam but their functionality is included here so there is no need to install them.

This package provides functions for the Skellam distribution, including: density (pmf), cdf, quantiles and regression.

Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).

This package provides a system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a â publication readyâ format. This is, the goal is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.

This package provides functions for the collection of 3D points and curves using a stereo camera setup.

"The Soil Texture Wizard" is a set of R functions designed to produce texture triangles (also called texture plots, texture diagrams, texture ternary plots), classify and transform soil textures data. These functions virtually allows to plot any soil texture triangle (classification) into any triangle geometry (isosceles, right-angled triangles, etc.). This set of function is expected to be useful to people using soil textures data from different soil texture classification or different particle size systems. Many (> 15) texture triangles from all around the world are predefined in the package. A simple text based graphical user interface is provided: soiltexture_gui().

Modern classes for tracking and movement data, building on sf spatial infrastructure, and early theoretical work from Turchin (1998, ISBN: 9780878938476), and Calenge et al. (2009) <doi:10.1016/j.ecoinf.2008.10.002>. Tracking data are series of locations with at least 2-dimensional spatial coordinates (x,y), a time index (t), and individual identification (id) of the object being monitored; movement data are made of trajectories, i.e. the line representation of the path, composed by steps (the straight-line segments connecting successive locations). sftrack is designed to handle movement of both living organisms and inanimate objects.

Take real or simulated data and salt it with errors commonly found in the wild, such as pseudo-OCR errors, Unicode problems, numeric fields with nonsensical punctuation, bad dates, etc.

This package performs simulation and inference of diffusion processes on circle. Stochastic correlation models based on circular diffusion models are provided. For details see Majumdar, S. and Laha, A.K. (2024) "Diffusion on the circle and a stochastic correlation model" <doi:10.48550/arXiv.2412.06343>.

Obtains lists of files of remote sensing collections for Southern Ocean surface properties. Commonly used data sources of sea surface temperature, sea ice concentration, and altimetry products such as sea surface height and sea surface currents are cached in object storage on the Pawsey Supercomputing Research Centre facility. Patterns of working to retrieve data from these object storage catalogues are described. The catalogues include complete collections of datasets Reynolds et al. (2008) "NOAA Optimum Interpolation Sea Surface Temperature (OISST) Analysis, Version 2.1" <doi:10.7289/V5SQ8XB5>, Spreen et al. (2008) "Artist Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice concentration" <doi:10.1029/2005JC003384>. In future releases helpers will be added to identify particular data collections and target specific dates for earth observation data for reading, as well as helpers to retrieve data set citation and provenance details. This work was supported by resources provided by the Pawsey Supercomputing Research Centre with funding from the Australian Government and the Government of Western Australia. This software was developed by the Integrated Digital East Antarctica program of the Australian Antarctic Division.

Estimate necessary sample sizes for comparing the location of data from two groups or categories when the distribution of the data is skewed. The package offers a non-parametric method for a Wilcoxon Mann-Whitney test of location shift as well as methods for several generalized linear models, for instance, Gamma regression.

Decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management, it can be used to generate and evaluate plans for surveying additional sites. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental algorithms. After generating such survey plans, they can be evaluated using conditions) and maximizing value of information. Please note that several functions depend on the Gurobi optimization software (available from <https://www.gurobi.com>). Additionally, the JAGS software (available from <https://mcmc-jags.sourceforge.io/>) is required to fit hierarchical generalized linear models. For further details, see Hanson et al. (2023) <doi:10.1111/1365-2664.14309>.

Simultaneous/joint diagonalization of local autocovariance matrices to estimate spatio-temporally uncorrelated random fields.

Fits a spatially discrete approximation to a log-Gaussian Cox process model for spatially aggregated disease count data, estimated by Monte Carlo Maximum Likelihood as in Christensen (2004) <doi:10.1198/106186004X2525> and Johnson, Diggle and Giorgi (2019) <doi:10.1002/sim.8339>. Performance-critical steps (aggregated correlation assembly, Metropolis-adjusted Langevin algorithm (MALA) sampling, the Monte Carlo likelihood, and the Kronecker-structured space-time likelihood) are implemented in C++ via RcppArmadillo'. Provides a one-line, glm'-like interface and statistical extensions including a nugget term, general Matern smoothness, raster and misaligned covariates, restricted spatial regression, importance-sampling diagnostics and re-anchored Monte Carlo maximum likelihood (MCML).

Some M-estimators for 1-dimensional location (Bisquare, ML for the Cauchy distribution, and the estimators from application of the smoothing principle introduced in Hampel, Hennig and Ronchetti (2011) to the above, the Huber M-estimator, and the median, main function is smoothm), and Pitman estimator.

An object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. It supports structuring of simulation scenarios (to avoid copy and paste) and aims to improve readability and re-usability of code.

This package provides functions for coarse-to-fine spatial and spatio-temporal modeling, enabling fast prediction, regression, and uncertainty quantification for moderate to large datasets. For methodological details, see Murakami et al. (2026) <doi:10.1111/gean.70034> and related work on generalized linear, downscaling, and dynamic spatio-temporal extensions.

Survey to collect data about the social and economic conditions of Indonesian society. This activity aims to include: As a data source for planning and evaluating national, sectoral development programs, and providing indicators for Sustainable Development Goals (TPB), National Medium Term Development Plan (RPJMN), and Nawacita, GDP/GRDP and annual Integrated Institutional Balance Sheet.

Implementations of the Single Transferable Vote counting system. By default, it uses the Cambridge method for surplus allocation and Droop method for quota calculation. Fractional surplus allocation and the Hare quota are available as options.

Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.

Converts the floor speeches of Uruguayan legislators, extracted from the parliamentary minutes, to tidy data.frame where each observation is the intervention of a single legislator.

This package provides a unified framework for the simultaneous testing of differential expression, variability, and skewness of genes using RNA-Seq data. The framework adopts a compositional data analysis approach for modelling RNA-Seq count data, applies the centered log-ratio transformation to obtain continuous variables, and uses the skew-normal distribution for statistical inference. Methods are described in Li and Khang (bioRxiv preprint, 2024, version 3) <doi:10.1101/2024.04.09.588804>.

Este paquete tiene la finalidad de ayudar a aprender de una forma interactiva, teniendo ejemplos y la posibilidad de resolver nuevos al mismo tiempo. Apuntes de clase interactivos.