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.

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 a suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the jamovi statistical spreadsheet (see <https://www.jamovi.org> for more information).

The age is estimated by calculating the Dirichlet Normal Energy (DNE) on the whole auricular surface and the apex of the auricular surface. It involves three estimation methods: principal component discriminant analysis (PCQDA), and principal component logistic regression analysis (PCLR) methods, principal component regression analysis with Southeast Asian (A_PCR), and principal component regression analysis with multipopulation (M_PCR). The package is created with the data from the Louis Lopes Collection in Lisbon, the 21st Century Identified Human Remains Collection in Coimbra, and the CAL Milano Cemetery Skeletal Collection in Milan, and the skeletal collection at Khon Kaen University (KKU) Human Skeletal Research Centre (HSRC), housed in the Department of Anatomy in the Faculty of Medicine at KKU in Khon Kaen.

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).

Takes an R expression and returns a job object with a $stop() method which can be called to terminate the background job. Also provides timeouts and other mechanisms for automatically terminating a background job. The result of the expression is available synchronously via $result or asynchronously with callbacks or through the promises package framework.

Offer procedures to download financial-economic time series data and enhanced procedures for computing the investment performance indices of Bacon (2004) <DOI:10.1002/9781119206309>.

Fits the joint model proposed by Henderson and colleagues (2000) <doi:10.1093/biostatistics/1.4.465>, but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project was funded by the Medical Research Council (Grant number MR/M013227/1).

Joint mean and dispersion effects models fit the mean and dispersion parameters of a response variable by two separate linear models, the mean and dispersion submodels, simultaneously. It also allows the users to choose either the deviance or the Pearson residuals as the response variable of the dispersion submodel. Furthermore, the package provides the possibility to nest the submodels in one another, if one of the parameters has significant explanatory power on the other. Wu & Li (2016) <doi:10.1016/j.csda.2016.04.015>.

This package performs Joins and Minus Queries on Excel Files fulljoinXL() Merges all rows of 2 Excel files based upon a common column in the files. innerjoinXL() Merges all rows from base file and join file when the join condition is met. leftjoinXL() Merges all rows from the base file, and all rows from the join file if the join condition is met. rightjoinXL() Merges all rows from the join file, and all rows from the base file if the join condition is met. minusXL() Performs 2 operations source-minus-target and target-minus-source If the files are identical all output files will be empty. Choose two Excel files via a dialog box, and then follow prompts at the console to choose a base or source file and columns to merge or minus on.

Install packages without attaching them. If a package it is already installed, it will be skipped.

The function get_parameters() is intended to be used within a docker container to read keyword arguments from a .json file automagically. A tool.yaml file contains specifications on these keyword arguments, which are then passed as input to containerized R tools in the [tool-runner framework](<https://github.com/hydrocode-de/tool-runner>). A template for a containerized R tool, which can be used as a basis for developing new tools, is available at the following URL: <https://github.com/VForWaTer/tool_template_r>.

This package provides a long-term forecast model called "Jubilee-Tectonic model" is implemented to forecast future returns of the U.S. stock market, Treasury yield, and gold price. The five-factor model forecasts the 10-year and 20-year future equity returns with high R-squared above 80 percent. It is based on linear growth and mean reversion characteristics in the U.S. stock market. This model also enhances the CAPE model by introducing the hypothesis that there are fault lines in the historical CAPE, which can be calibrated and corrected through statistical learning. In addition, it contains a module for business cycles, optimal interest rate, and recession forecasts.

This package provides functions to extract joint planes from 3D triangular mesh derived from point cloud and makes data available for structural analysis.

This package provides a set of helper functions to conduct joint-significance tests for mediation analysis, as recommended by Yzerbyt, Muller, Batailler, & Judd. (2018) <doi:10.1037/pspa0000132>.

Calculate statistical significance of Jaccard/Tanimoto similarity coefficients for binary data.

This package provides methods to perform Joint graph Regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization ('jrSiCKLSNMF', pronounced "junior sickles NMF") on quality controlled single-cell multimodal omics count data. jrSiCKLSNMF specifically deals with dual-assay scRNA-seq and scATAC-seq data. This package contains functions to extract meaningful latent factors that are shared across omics modalities. These factors enable accurate cell-type clustering and facilitate visualizations. Methods for pre-processing, clustering, and mini-batch updates and other adaptations for larger datasets are also included. For further details on the methods used in this package please see Ellis, Roy, and Datta (2023) <doi:10.3389/fgene.2023.1179439>.

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 tools to use API such as e-Stat (<https://www.e-stat.go.jp/>), the portal site for Japanese government statistics, and RESAS (Regional Economy and Society Analyzing System, <https://resas.go.jp>).

Structure and formatting requirements for clinical trial table and listing outputs vary between pharmaceutical companies. junco provides additional tooling for use alongside the rtables', rlistings and tern packages when creating table and listing outputs. While motivated by the specifics of Johnson and Johnson Clinical and Statistical Programming's table and listing shells, junco provides functionality that is general and reusable. Major features include a) alternative and extended statistical analyses beyond what tern supports for use in standard safety and efficacy tables, b) a robust production-grade Rich Text Format (RTF) exporter for both tables and listings, c) structural support for spanning column headers and risk difference columns in tables, and d) robust font-aware automatic column width algorithms for both listings and tables.

This package implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), and characteristic pattern discovery along with interpretable time series classification.

This package provides tools to access the J-STAGE WebAPI and retrieve information published on J-STAGE <https://www.jstage.jst.go.jp/browse/-char/ja>.

Miscellaneous tools and functions, including: generate descriptive statistics tables, format output, visualize relations among variables or check distributions, and generic functions for residual and model diagnostics.

This package provides a function allowing to normalize a JSON string, for example by adding double quotes around the keys when they are missing. Also provides RStudio addins for the same purpose.