Artifacts using Tools (13,792)

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RSQLite connects SQLite and Renjin via a DBI-like interface

This package provides an easy and simple way to read, write and display bitmap images stored in the PNG format. It can read and write both files and in-memory raw vectors.

Functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".

Model-robust standard error estimators for cross-sectional, time series, clustered, panel, and longitudinal data.

A general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, ...

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.

Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.

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 Schafer and Strimmer (2005) <DOI:10.2202/1544-6115.1175> and Opgen-Rhein and Strimmer (2007) <DOI:10.2202/1544-6115.1252>. 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 ...

Set of tools for manipulating geographic data. It includes binary access to 'GSHHG' shoreline files. The package also provides interface wrappers for exchanging spatial objects with packages such as 'PBSmapping', 'spatstat', 'maps', 'RArcInfo', and others.