5 packages on CRAN
Contains methods for creating multivariate/multidimensional interpolations of functions on a hypercube. If available through fftw3, the DCT-II/FFT is used to compute coefficients for a Chebyshev interpolation. Other interpolation methods for arbitrary Cartesian grids are also provided, a piecewise multilinear, and the Floater-Hormann barycenter method. For scattered data polyharmonic splines with a linear term is provided. The time-critical parts are written in C for speed. All interpolants are parallelized if used to evaluate more than one point.
Estimation of piecewise constant mixed proportional hazard competing risk model with NPMLE. The model is described in S. Gaure et al. (2007) <doi:10.1016/j.jeconom.2007.01.015>, J. Heckman and B. Singer (1984) <doi:10.2307/1911491>, and B.G. Lindsay (1983) <doi:10.1214/aos/1176346059>.
Transforms away factors with many levels prior to doing an OLS. Useful for estimating linear models with multiple group fixed effects, and for estimating linear models which uses factors with many levels as pure control variables. Includes support for instrumental variables, conditional F statistics for weak instruments, robust and multi-way clustered standard errors, as well as limited mobility bias correction.
A C/C++ based package for advanced data transformation in R that is extremely fast, flexible and parsimonious to code with and programmer friendly. It is well integrated with 'dplyr', 'plm' and 'data.table'. --- Key Features: --- (1) Advanced data programming: A full set of fast statistical functions supporting grouped and weighted computations on vectors, matrices and data frames. Fast (ordered) and programmable grouping, factor generation, manipulation of data frames and data object conversions. (2) Advanced aggregation: Fast and easy multi-data-type, multi-function, weighted, parallelized and fully customized data aggregation. (3) Advanced transformations: Fast (grouped, weighted) replacing and sweeping out of statistics, scaling / standardizing, centering (i.e. between and within transformations), higher-dimensional centering (i.e. multiple fixed effects transformations), linear prediction and partialling-out. (4) Advanced time-computations: Fast (sequences of) lags / leads, and (lagged / leaded, iterated, quasi-, log-) differences and growth rates on (unordered) time-series and panel data. Multivariate auto, partial and cross-correlation functions for panel data. Panel data to (ts-)array conversions. (5) List processing: (Recursive) list search / identification, extraction / subsetting, data-apply, and generalized row-binding / unlisting in 2D. (6) Advanced data exploration: Fast (grouped, weighted, panel-decomposed) summary statistics for complex multilevel / panel data.
R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.