Proposes a coarse-to-fine optimization of a recommending system based on deep-neural networks using tensorflow'.

This package provides method used to check whether data have outlier in efficiency measurement of big samples with data envelopment analysis (DEA). In this jackstrap method, the package provides two criteria to define outliers: heaviside and k-s test. The technique was developed by Sousa and Stosic (2005) "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers." <doi:10.1007/s11123-005-4702-4>.

This package provides a GUI interface for automating data extraction from multiple images containing scatter and bar plots, semi-automated tools to tinker with extraction attempts, and a fully-loaded point-and-click manual extractor with image zoom, calibrator, and classifier. Also provides detailed and R-independent extraction reports as fully-embedded .html records.

The free and open a statistical spreadsheet jamovi (<https://www.jamovi.org>) aims to make statistical analyses easy and intuitive. jamovi produces syntax that can directly be used in R (in connection with the R-package jmv'). Having import / export routines for the data files jamovi produces ('.omv') permits an easy transfer of data and analyses between jamovi and R.

Download and post process the infectious disease case data from Japan Institute for Health Security. Also the package included ready-to-analyse datasets. See the data source website for further details <https://id-info.jihs.go.jp/>.

Implementation of some unit and area level EBLUP estimators as well as the estimators of their MSE also under heteroscedasticity. The package further documents the publications Breidenbach and Astrup (2012) <DOI:10.1007/s10342-012-0596-7>, Breidenbach et al. (2016) <DOI:10.1016/j.rse.2015.07.026> and Breidenbach et al. (2018 in press). The vignette further explains the use of the implemented functions.

The Impact Factor of a journal reported by Journal Citation Reports ('JCR') of Clarivate Analytics is provided. The impact factor is available for those journals only that were included Journal Citation Reports JCR'.

This package provides tools to explore and summarize relationship patterns between variables across one or multiple datasets. The package relies on efficient sampling strategies to estimate pairwise associations and supports quick exploratory data analysis for large or heterogeneous data sources.

Tool for diagnosing table joins. It combines the speed of `collapse` and `data.table`, the flexibility of `dplyr`, and the diagnosis and features of the `merge` command in `Stata`.

Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues <doi:10.1093/biostatistics/1.4.465> (single event time) and by Williamson and colleagues (2008) <doi:10.1002/sim.3451> (competing risks events time) to a single continuous repeated measure. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-varying covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by a latent Gaussian process. The model is estimated using am Expectation Maximization algorithm. Some plotting functions and the variogram are also included. This project is funded by the Medical Research Council (Grant numbers G0400615 and MR/M013227/1).

Reproducible work requires a record of where every statistic originated. When writing reports, some data is too big to load in the same environment and some statistics take a while to compute. This package offers a way to keep notes on statistics, simple functions, and small objects. Notepads can be locked to avoid accidental updates. Notepads keep track of who added the notes and when the notes were added. A simple text representation is used to allow for clear version histories.

Scientific journal numeric formatting policies implemented in code. Emphasis on formatting mean/upper/lower sets of values to pasteable text for journal submission. For example c(2e6, 1e6, 3e6) becomes "2.00 million (1.00--3.00)". Lancet and Nature have built-in styles for rounding and punctuation marks. Users may extend journal styles arbitrarily. Four metrics are supported; proportions, percentage points, counts and rates. Magnitudes for all metrics are discovered automatically.

This package provides a Wrapper for the Node.js Jdenticon <https://jdenticon.com/> Library. Uses esbuild <https://esbuild.github.io/> to reduce user dependencies.

This package provides tools for competing risks trials that allow simultaneous inference on recovery and mortality endpoints. Provides data preparation helpers, standard cumulative incidence estimators (restricted mean time gained/lost), and severity weighted extensions that integrate longitudinal ordinal outcomes to summarise treatment benefit. Methods follow Wen, Hu, and Wang (2023) Biometrics 79(3):1635-1645 <doi:10.1111/biom.13752>.

This package provides tools for using the API of e-Stat (<https://www.e-stat.go.jp/>), a portal site for Japanese government statistics. Includes functions for automatic query generation, data collection and formatting.

Calculate statistical significance of Jaccard/Tanimoto similarity coefficients.

Minimal and memory efficient implementation of the junction tree algorithm using the Lauritzen-Spiegelhalter scheme; S. L. Lauritzen and D. J. Spiegelhalter (1988) <https://www.jstor.org/stable/2345762?seq=1>. The jti package is part of the paper <doi:10.18637/jss.v111.i02>.

This package implements the classical Jacobi algorithm for the eigenvalues and eigenvectors of a real symmetric matrix, both in pure R and in C++ using Rcpp'. Mainly as a programming example for teaching purposes.

Metaprogramming utilities for converting R regression model formulae to equivalents in Julia <doi:10.1137/141000671>, via modifications to the abstract syntax tree. Supports translations in zero correlation random effects syntax, protection of expressions to be evaluated as-is, interaction terms, and more. Accepts strings or R formula objects and returns modified R formula objects where possible (or a modified string, if not a valid formula in R).

Fits joint species distribution models ('jSDM') in a hierarchical Bayesian framework (Warton and al. 2015 <doi:10.1016/j.tree.2015.09.007>). The Gibbs sampler is written in C++'. It uses Rcpp', Armadillo and GSL to maximize computation efficiency.

Generates image data for fractals (Julia and Mandelbrot sets) on the complex plane in the given region and resolution. Benoit B Mandelbrot (1982).

This package provides methods for fast segmentation of multivariate signals into piecewise constant profiles and for generating realistic copy-number profiles. A typical application is the joint segmentation of total DNA copy numbers and allelic ratios obtained from Single Nucleotide Polymorphism (SNP) microarrays in cancer studies. The methods are described in Pierre-Jean, Rigaill and Neuvial (2015) <doi:10.1093/bib/bbu026>.

This package provides a framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).

This package provides a function collection to extract metadata, sectioned text and study characteristics from scientific articles in NISO-JATS format. Articles in PDF format can be converted to NISO-JATS with the Content ExtRactor and MINEr ('CERMINE', <https://github.com/CeON/CERMINE>). For convenience, two functions bundle the extraction heuristics: JATSdecoder() converts NISO-JATS'-tagged XML files to a structured list with elements title, author, journal, history, DOI', abstract, sectioned text and reference list. study.character() extracts multiple study characteristics like number of included studies, statistical methods used, alpha error, power, statistical results, correction method for multiple testing, software used. The function get.stats() extracts all statistical results from text and recomputes p-values for many standard test statistics. It performs a consistency check of the reported with the recalculated p-values. An estimation of the involved sample size is performed based on textual reports within the abstract and the reported degrees of freedom within statistical results. In addition, the package contains some useful functions to process text (text2sentences(), text2num(), ngram(), strsplit2(), grep2()). See Böschen, I. (2021) <doi:10.1007/s11192-021-04162-z> Böschen, I. (2021) <doi:10.1038/s41598-021-98782-3>, Böschen, I. (2023) <doi:10.1038/s41598-022-27085-y>, and Böschen, I. (2024) <doi:10.48550/arXiv.2408.07948>.