## Found **23** results

Classes and methods for dense and sparse matrices and operations on them using 'LAPACK' and 'SuiteSparse'.

Last Release on Aug 14, 2018

Implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The details of the method are explained in Sch\"afer and Strimmer (2005) and Opgen-Rhein and Strimmer (2007). The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also ...

Last Release on Jan 20, 2018

'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' ...

Last Release on Aug 14, 2018

## 5. MIICD

org.renjin.cran » MIICDGPL

Implements multiple imputation for proportional hazards regression with interval censored data or proportional sub-distribution hazards regression for interval censored competing risks data. The main functions allow to estimate survival function, cumulative incidence function, Cox and Fine & Gray regression coefficients and associated variance-covariance matrix. 'MIICD' functions call 'Surv', 'survfit' and 'coxph' from the 'survival' package, 'crprep' from the 'mstate' package, and 'mvrnorm' from the 'MASS' ...

Last Release on Jan 20, 2018

## 6. Filematrix

org.renjin.cran » filematrixLGPL

Interface for working with large matrices stored in files, not in computer memory. Supports multiple data types (double, integer, logical and raw) of different sizes (e.g. 4, 2, or 1 byte integers). Access to parts of the matrix is done by indexing, exactly as with usual R matrices. Supports very large matrices (tested on 1 terabyte matrix), allowing for more than 2^32 rows or columns. Cross-platform as the package has R code only, no C/C++.

Last Release on Jan 20, 2018

Efficient implementation of Friedman's boosting algorithm with l2-loss function and coordinate direction (design matrix columns) basis functions.

Last Release on Jan 20, 2018

Calculate and plot scattering matrix coefficients for plane waves at interface.

Last Release on Jan 20, 2018

A collection of matrix functions for teaching and learning matrix linear algebra as used in multivariate statistical methods. These functions are mainly for tutorial purposes in learning matrix algebra ideas using R. In some cases, functions are provided for concepts available elsewhere in R, but where the function call or name is not obvious. In other cases, functions are provided to show or demonstrate an algorithm.

Last Release on Jan 20, 2018

## 10. Eigenmodel

This package estimates the parameters of a model for symmetric relational data (e.g., the above-diagonal part of a square matrix), using a model-based eigenvalue decomposition and regression. Missing data is accomodated, and a posterior mean for missing data is calculated under the assumption that the data are missing at random. The marginal distribution of the relational data can be arbitrary, and is fit with an ordered probit specification.

Last Release on Jan 20, 2018