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Implementation of methods Extremum Surface Estimator (ESE) and Extremum Distance Estimator (EDE) to identify the inflection point of a curve . Christopoulos, DT (2014) <doi:10.48550/arXiv.1206.5478> . Christopoulos, DT (2016) <https://demovtu.veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf> . Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> .
When added to an existing shiny app, users may subset any developer-chosen R data.frame on the fly. That is, users are empowered to slice & dice data by applying multiple (order specific) filters using the AND (&) operator between each, and getting real-time updates on the number of rows effected/available along the way. Thus, any downstream processes that leverage this data source (like tables, plots, or statistical procedures) will re-render after new filters are applied. The shiny moduleâ s user interface has a minimalist aesthetic so that the focus can be on the data & other visuals. In addition to returning a reactive (filtered) data.frame, IDEAFilter as also returns dplyr filter statements used to actually slice the data.
Independent vector analysis (IVA) is a blind source separation (BSS) model where several datasets are jointly unmixed. This package provides several methods for the unmixing together with some performance measures. For details, see Anderson et al. (2011) <doi:10.1109/TSP.2011.2181836> and Lee et al. (2007) <doi:10.1016/j.sigpro.2007.01.010>.
Convert between bookmaker odds and probabilities. Eight different algorithms are available, including basic normalization, Shin's method (Hyun Song Shin, (1992) <doi:10.2307/2234526>), and others.
This package provides tools to analyze point patterns in space occurring over planar network structures derived from graph-related intensity measures for undirected, directed, and mixed networks. This package is based on the following research: Eckardt and Mateu (2018) <doi:10.1080/10618600.2017.1391695>. Eckardt and Mateu (2021) <doi:10.1007/s11749-020-00720-4>.
It provides multiple functions that are useful for ecological research and teaching statistics to ecologists. It is based on data analysis courses offered at the Instituto de Ecologà a AC (INECOL). For references and published evidence see, Manrique-Ascencio, et al (2024) <doi:10.1111/gcb.17282>, Manrique-Ascencio et al (2024) <doi:10.1111/plb.13683>, Ruiz-Guerra et al(2017) <doi:10.17129/botsci.812>, Juarez-Fragoso et al (2024) <doi:10.1007/s10980-024-01809-z>, Papaqui-Bello et al (2024) <doi:10.13102/sociobiology.v71i2.10503>.
Running Focused Identification of the Germplasm Strategy (FIGS) to make best subsets from Genebank Collection.
This package implements the Information Matrix test for regression models following Cameron, A. C., & Trivedi, P. K. (1990) <https://cameron.econ.ucdavis.edu/research/imtest_impliedalternatives_ucdwp372.pdf> Decomposes the test into components for heteroscedasticity, skewness, and kurtosis to diagnose specific forms of misspecification. Provides both overall and component-wise statistics for model assessment.
Models, analyzes, and forecasts financial intraday signals. This package currently supports a univariate state-space model for intraday trading volume provided by Chen (2016) <doi:10.2139/ssrn.3101695>.
Calculate the injury severity score (ISS) based on the dictionary in ICDPIC from <https://ideas.repec.org/c/boc/bocode/s457028.html>. The original code was written in STATA 11'. The original STATA code was written by David Clark, Turner Osler and David Hahn. I implement the same logic for easier access. Ref: David E. Clark & Turner M. Osler & David R. Hahn, 2009. "ICDPIC: Stata module to provide methods for translating International Classification of Diseases (Ninth Revision) diagnosis codes into standard injury categories and/or scores," Statistical Software Components S457028, Boston College Department of Economics, revised 29 Oct 2010.
Simple plotting function(s) for exploratory data analysis with flexible options allowing for easy plot customisation. The goal is to make it easy for beginners to start exploring a dataset through simple R function calls, as well as provide a similar interface to summary statistics and inference information. Includes functionality to generate interactive HTML-driven graphs. Used by iNZight', a graphical user interface providing easy exploration and visualisation of data for students of statistics, available in both desktop and online versions.
Analyst oriented utility functions to handle the different quirks of the Israeli CBS municipal data, harmonize id's and bring together data points from different years.
This package provides tools to scrape, clean, and analyze football player data from Indonesian leagues and perform similarity-based scouting analysis using standardized numeric features. The similarity approach follows common vector-space methods as described in Manning et al. (2008, ISBN:9780521865715) and Salton et al. (1975, <doi:10.1145/361219.361220>).
One function to read files. One function to write files. One function to direct plots to screen or file. Automatic file format inference and directory structure creation.
The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 <doi:10.1017/RDC.2020.68>) are provided here in a single data package, together with previous IntCal curves (IntCal13, IntCal09, IntCal04, IntCal98) and postbomb curves. Also provided are functions to copy the curves into memory, and to plot the curves and their underlying data, as well as functions to calibrate radiocarbon dates.
This package provides a systematic framework for integrating multiple modalities of assays profiled on the same set of samples. The goal is to identify genes that are altered in cancer either marginally or consistently across different assays. The heterogeneity among different platforms and different samples are automatically adjusted so that the overall alteration magnitude can be accurately inferred. See Tong and Coombes (2012) <doi:10.1093/bioinformatics/bts561>.
Generates random numbers corresponding to the events on a Poisson point process with changing event rates. This includes the possibility to incorporate additional information such as the number of events occurring or the location of an already known event. It can also generate the probability density functions of specific events in the cases where additional information is available. Based on Hohmann (2019) <arXiv:1901.10754>.
This package provides a port of Python's excellent itertools module to R for efficient looping.
This package provides function to read data from the Igor Pro data analysis program by Wavemetrics'. The data formats supported are Igor packed experiment format ('pxp') and Igor binary wave ('ibw'). See: <https://www.wavemetrics.com/> for details. Also includes functions to load special pxp files produced by the Igor Pro Neuromatic and Nclamp packages for recording and analysing neuronal data. See <https://github.com/SilverLabUCL/NeuroMatic> for details.
The inti package is part of the inkaverse project for developing different procedures and tools used in plant science and experimental designs. The mean aim of the package is to support researchers during the planning of experiments and data collection (tarpuy()), data analysis and graphics (yupana()) , and scientific writing. Learn more about the inkaverse project at <https://inkaverse.com/>.
Runs classical item analysis for multiple-choice test items and polytomous items (e.g., rating scales). The statistics reported in this package can be found in any measurement textbook such as Crocker and Algina (2006, ISBN:9780495395911).
An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website <https://www.ipums.org>.
Quick indexation of any type of vector or of any combination of those. Indexation turns a vector into an integer vector going from 1 to the number of unique elements. Indexes are important building blocks for many algorithms. The method is described at <https://github.com/lrberge/indexthis/>.
Estimate the relative abundance of tissue-infiltrating immune subpopulations abundances using gene expression data.