This package provides a mainly instrumental package meant to allow other packages whose core is written in C++ to read, write and manipulate matrices in a binary format so that the memory used for them is no more than strictly needed. Its functionality is already inside parallelpam and scellpam', so if you have installed any of these, you do not need to install jmatrix'. Using just the needed memory is not always true with R matrices or vectors, since by default they are of double type. Trials like the float package have been done, but to use them you have to coerce a matrix already loaded in R memory to a float matrix, and then you can delete it. The problem comes when your computer has not memory enough to hold the matrix in the first place, so you are forced to load it by chunks. This is the problem this package tries to address (with partial success, but this is a difficult problem since R is not a strictly typed language, which is anyway quite hard to get in an interpreted language). This package allows the creation and manipulation of full, sparse and symmetric matrices of any standard data type.

This package provides functions to standardize and whiten data, and to perform Principal Component Analysis (PCA). The main advantage of this package over alternatives like prcomp() is, that jvcoords makes it easy to convert (additional) data between the original and the transformed coordinates. The package also provides a class coords, which can represent affine coordinate transformations. This class forms the basis of the transformations provided by the package, but can also be used independently. The implementation has been optimized to be of comparable speed (and sometimes even faster) than existing alternatives.

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).

This package contains functions for fitting a joinpoint proportional hazards model to relative survival or cause-specific survival data, including estimates of joinpoint years at which survival trends have changed and trend measures in the hazard and cumulative survival scale. See Yu et al.(2009) <doi:10.1111/j.1467-985X.2009.00580.x>.

Automatic disaggregation of small-area population estimates by demographic groups (e.g., age, sex, race, marital status, educational level, etc) along with the estimates of uncertainty, using advanced Bayesian statistical modelling approaches based on integrated nested Laplace approximation (INLA) Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> and stochastic partial differential equation (SPDE) methods Lindgren et al. (2011) <doi:10.1111/j.1467-9868.2011.00777.x>. The package implements hierarchical Bayesian modeling frameworks for small area estimation as described in Leasure et al. (2020) <doi:10.1073/pnas.1913050117> and Nnanatu et al. (2025) <doi:10.1038/s41467-025-59862-4>.

This package provides tools are provided to streamline Bayesian analyses in JAGS using the jagsUI package. Included are functions for extracting output in simpler format, functions for streamlining assessment of convergence, and functions for producing summary plots of output. Also included is a function that provides a simple template for running JAGS from R'. Referenced materials can be found at <DOI:10.1214/ss/1177011136>.

Evaluation of the Jacobi theta functions and related functions: Weierstrass elliptic function, Weierstrass sigma function, Weierstrass zeta function, Klein j-function, Dedekind eta function, lambda modular function, Jacobi elliptic functions, Neville theta functions, Eisenstein series, lemniscate elliptic functions, elliptic alpha function, Rogers-Ramanujan continued fractions, and Dixon elliptic functions. Complex values of the variable are supported.

This package implements the basic financial analysis functions similar to (but not identical to) what is available in most spreadsheet software. This includes finding the IRR and NPV of regularly spaced cash flows and annuities. Bond pricing and YTM calculations are included. In addition, Black Scholes option pricing and Greeks are also provided.

This package provides a highly configurable jQuery plugin offering a simple interface to create complex queries/filters in Shiny'. The outputted rules can easily be parsed into a set of R and/or SQL queries and used to filter data. Custom parsing of the rules is also supported. For more information about jQuery QueryBuilder see <https://querybuilder.js.org/>.

Estimate risk caused by two extreme and dependent forcing variables using bivariate extreme value models as described in Zheng, Westra, and Sisson (2013) <doi:10.1016/j.jhydrol.2013.09.054>; Zheng, Westra and Leonard (2014) <doi:10.1002/2013WR014616>; Zheng, Leonard and Westra (2015) <doi:10.2166/hydro.2015.052>.

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.

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>.

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 performs power calculations for joint modeling of longitudinal and survival data with k-th order trajectories when the variance-covariance matrix, Sigma_theta, is unknown.

This package provides an R interface to the JBrowse 2 genome browser. Enables embedding a JB2 genome browser in a Shiny app or R Markdown document. The browser can also be launched from an interactive R console. The browser can be loaded with a variety of common genomics data types, and can be used with a custom theme.

This package provides functions for grid square codes in Japan (<https://www.stat.go.jp/english/data/mesh/index.html>). Generates the grid square codes from longitude/latitude, geometries, and the grid square codes of different scales, and vice versa.

Aids in the calculation and visualization of regions of non-significance using the Johnson-Neyman technique and its extensions as described by Bauer and Curran (2005) <doi:10.1207/s15327906mbr4003_5> to assess the influence of categorical and continuous moderators. Allows correcting for phylogenetic relatedness.

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 an interface to Jamendo API <https://developer.jamendo.com/v3.0>. Pull audio, features and other information for a given Jamendo user (including yourself!) or enter an artist's -, album's -, or track's name and retrieve the available information in seconds.

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>.

Fitting and analyzing a Joint Trait Distribution Model. The Joint Trait Distribution Model is implemented in the Bayesian framework using conjugate priors and posteriors, thus guaranteeing fast inference. In particular the package computes joint probabilities and multivariate confidence intervals, and enables the investigation of how they depend on the environment through partial response curves. The method implemented by the package is described in Poggiato et al. (2023) <doi:10.1111/geb.13706>.

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/>.

Leverages the yum package to implement a YAML ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https://yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.

Graphics device routing all graphics commands to a Java program. The actual functionality of the JavaGD depends on the Java-side implementation. Simple AWT and Swing implementations are included.