Title: Superfast Likelihood Inference for Stationary Gaussian Time
Authors@R: c(person("Yun", "Ling", role = "aut"),
Description: Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations.  This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300.  Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo.  The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.
Imports: stats, methods, Rcpp (>= 0.12.7), fftw
Suggests: knitr, rmarkdown, testthat, mvtnorm, numDeriv

Imports: stats, methods, R6, Rcpp (>= 0.12.7), fftw

Description: This package implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Suggests: arm, BayesTree, caret, class, e1071, earth, gam, gbm,
genefilter, ggplot2, glmnet, Hmisc, ipred, lattice, LogicReg,
MASS, mda, mlbench, nnet, parallel, party, polspline, quadprog,
randomForest, rpart, SIS, spls, stepPlr, sva

Suggests: arm, caret, class, cvAUC, e1071, earth, gam, gbm, genefilter,
ggplot2, glmnet, Hmisc, ipred, lattice, LogicReg, MASS, mda,
mlbench, nloptr, nnet, parallel, party, polspline, quadprog,
randomForest, ROCR, rpart, SIS, spls, stepPlr, sva

Author: Eric Polley, Erin LeDell, Mark van der Laan
Description: Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Suggests: arm, caret, class, e1071, earth, gam, gbm, genefilter,
mlbench, nloptr, nnet, party, polspline, quadprog,

Authors@R: c(person("Eric", "Polley", email = "polley.eric@mayo.edu", role = c("aut", "cre")), person("Erin", "LeDell", role = c("aut")), person("Chris", "Kennedy", role = c("aut")), person("Sam", "Lendle", role = c("ctb")), person("Mark", "van der Laan", role = c("aut", "ths")))
Description: Implements the super learner prediction method and contains a
library of prediction algorithms to be used in the super learner.
Suggests: arm, bartMachine, caret, class, e1071, earth, gam, gbm,
MASS, mda, mlbench, nloptr, nnet, party, polspline, quadprog,
randomForest, ROCR, rpart, SIS, spls, stepPlr, sva, testthat,