This package provides functions to access, search and download spacetime earth observation data via SpatioTemporal Asset Catalog (STAC). This package supports the version 1.0.0 (and older) of the STAC specification (<https://github.com/radiantearth/stac-spec>). For further details see Simoes et al. (2021) <doi:10.1109/IGARSS47720.2021.9553518>.

Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors. Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx). Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order), DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity). Also quaternion and other useful functions. Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva.

For any two way feature-set from a pair of pre-processed omics data, 3 different true discovery proportions (TDP), namely pairwise-TDP, column-TDP and row-TDP are calculated. Due to embedded closed testing procedure, the choice of feature-sets can be changed infinite times and even after seeing the data without any change in type I error rate. For more details refer to Ebrahimpoor et al., (2024) <doi:10.48550/arXiv.2410.19523>.

Circular / ring buffers in R and C. There are a couple of different buffers here with different implementations that represent different trade-offs.

Loads Blackrock <https://blackrockneurotech.com> neural signal data files into the memory, provides utility tools to extract the data into common formats such as plain-text tsv and HDF5'.

Data with irregular spatial support, such as runoff related data or data from administrative units, can with rtop be interpolated to locations without observations with the top-kriging method. A description of the package is given by Skøien et al (2014) <doi:10.1016/j.cageo.2014.02.009>.

This package provides access to Rangeland Analysis Platform (RAP) products <https://rangelands.app/products> for arbitrary extents via GDAL virtual file system.

Climacell is a weather platform that provides hyper-local forecasts and weather data. This package enables the user to query the core layers of the time line interface of the Climacell v4 API <https://www.climacell.co/weather-api/>. This package requires a valid API key. See vignettes for instructions on use.

The Stuttgart Neural Network Simulator (SNNS) is a library containing many standard implementations of neural networks. This package wraps the SNNS functionality to make it available from within R. Using the RSNNS low-level interface, all of the algorithmic functionality and flexibility of SNNS can be accessed. Furthermore, the package contains a convenient high-level interface, so that the most common neural network topologies and learning algorithms integrate seamlessly into R.

Integrated tools to support rigorous and well documented data harmonization based on Maelstrom Research guidelines. The package includes functions to assess and prepare input elements, apply specified processing rules to generate harmonized datasets, validate data processing and identify processing errors, and document and summarize harmonized outputs. The harmonization process is defined and structured by two key user-generated documents: the DataSchema (specifying the list of harmonized variables to generate across datasets) and the Data Processing Elements (specifying the input elements and processing algorithms to generate harmonized variables in DataSchema formats). The package was developed to address key challenges of retrospective data harmonization in epidemiology (as described in Fortier I and al. (2017) <doi:10.1093/ije/dyw075>) but can be used for any data harmonization initiative.

Storing huge data in RData format causes problems because of the necessity to load the whole file to the memory in order to access and manipulate objects inside such file; rtape is a simple solution to this problem. The package contains several wrappers of R built-in serialize/unserialize mechanism allowing user to quickly append objects to a tape-like file and later iterate over them requiring only one copy of each stored object to reside in memory a time.

Enhances the R Optimization Infrastructure ('ROI') package with the possibility to obtain multiple solutions for linear problems with binary variables. The main function is copied (with small modifications) from the relations package.

This package provides methods for calculating diversity indices on numerical matrices, based on information theory, following Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039> and Rocchini et al. (2021) <doi:10.1101/2021.01.23.427872>.

Regularised discriminant analysis functions. The classical regularised discriminant analysis proposed by Friedman in 1989, including cross-validation, of which the linear and quadratic discriminant analyses are special cases. Further, the regularised maximum likelihood linear discriminant analysis, including cross-validation. References: Friedman J.H. (1989): "Regularized Discriminant Analysis". Journal of the American Statistical Association 84(405): 165--175. <doi:10.2307/2289860>. Friedman J., Hastie T. and Tibshirani R. (2009). "The elements of statistical learning", 2nd edition. Springer, Berlin. <doi:10.1007/978-0-387-84858-7>. Tsagris M., Preston S. and Wood A.T.A. (2016). "Improved classification for compositional data using the alpha-transformation". Journal of Classification, 33(2): 243--261. <doi:10.1007/s00357-016-9207-5>.

Provide function for get data from YouTube Data API <https://developers.google.com/youtube/v3/docs/>, YouTube Analytics API <https://developers.google.com/youtube/analytics/reference/> and YouTube Reporting API <https://developers.google.com/youtube/reporting/v1/reports>.

EZR (Easy R) adds a variety of statistical functions, including survival analyses, ROC analyses, metaanalyses, sample size calculation, and so on, to the R commander. EZR enables point-and-click easy access to statistical functions, especially for medical statistics. EZR is platform-independent and runs on Windows, Mac OS X, and UNIX. Its complete manual is available only in Japanese (Chugai Igakusha, ISBN: 978-4-498-10918-6, Nankodo, ISBN: 978-4-524-21861-5, Ohmsha, ISBN: 978-4-274-22632-8), but an report that introduced the investigation of EZR was published in Bone Marrow Transplantation (Nature Publishing Group) as an Open article. This report can be used as a simple manual. It can be freely downloaded from the journal website as shown below. This report has been cited in more than 14,000 scientific articles.

The ecocrop model estimates environmental suitability for plants using a limiting factor approach for plant growth following Hackett (1991) <doi:10.1007/BF00045728>. The implementation in this package is fast and flexible: it allows for the use of any (environmental) predictor variable. Predictors can be either static (for example, soil pH) or dynamic (for example, monthly precipitation).

Minirhizotrons are widely used to observe and explore roots and their growth. This package provides the means to stitch images and divide them into depth layers. Please note that this R package was developed alongside the following manuscript: Stitching root scans and extracting depth layer information -- a workflow and practical examples, S. Kersting, L. Knüver, and M. Fischer. The manuscript is currently in preparation and should be citet as soon as it is available. This project was supported by the project ArtIGROW, which is a part of the WIR!-Alliance ArtIFARM â Artificial Intelligence in Farming funded by the German Federal Ministry of Research, Technology and Space (No. 03WIR4805).

Simulates the dynamics of exploited fish populations using the Jones modification of the Beverton-Holt equilibrium yield equation to compute yield-per-recruit and dynamic pool models (Ricker 1975) <https://publications.gc.ca/site/eng/480738/publication.html>. Allows users to evaluate minimum, slot, and inverted length limits on exploited fisheries using specified life history parameters. Users can simulate population under a variety of conditional fishing mortality and conditional natural mortality. Calculated quantities include number of fish harvested and dying naturally, mean weight and length of fish harvested, number of fish that reach specified lengths of interest, total number of fish and biomass in the population, and stock density indices.

This package provides an interface between R and PostGIS'-enabled PostgreSQL databases to transparently transfer spatial data. Both vector (points, lines, polygons) and raster data are supported in read and write modes. Also provides convenience functions to execute common procedures in PostgreSQL/PostGIS'.

The key function get_vintage_data() returns a dataframe and is the window into the Census Bureau API requiring just a dataset name, vintage(year), and vector of variable names for survey estimates/percentages. Other functions assist in searching for available datasets, geographies, group/variable concepts of interest. Also provided are functions to access and layer (via standard piping) displayable geometries for the US, states, counties, blocks/tracts, roads, landmarks, places, and bodies of water. Joining survey data with many of the geometry functions is built-in to produce choropleth maps.

NanoString nCounter is a medium-throughput platform that measures gene or microRNA expression levels. Here is a publication that introduces this platform: Malkov (2009) <doi:10.1186/1756-0500-2-80>. Here is the webpage of NanoString nCounter where you can find detailed information about this platform <https://www.nanostring.com/scientific-content/technology-overview/ncounter-technology>. It has great clinical application, such as diagnosis and prognosis of cancer. Implements integrated system of random-coefficient hierarchical regression model to normalize data from NanoString nCounter platform so that noise from various sources can be removed.

Collection of tools to develop options strategies, value option contracts using the Black-Scholes-Merten option pricing model and calculate the option Greeks. Hull, John C. "Options, Futures, and Other Derivatives" (1997, ISBN:0-13-601589-1). Fischer Black, Myron Scholes (1973) "The Pricing of Options and Corporate Liabilities" <doi:10.1086/260062>.

Data for the examples and exercises in the book "R by Example". Jim Albert and Maria Rizzo (2012, ISBN 978-1-4614-1365-3).