Superfast Likelihood Inference for Stationary Gaussian Time
Series
c(person("Yun", "Ling", role = "aut"),
person("Martin", "Lysy",
email = "mlysy@uwaterloo.ca",
role = c("aut", "cre")))
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.
knitr, rmarkdown, testthat, mvtnorm, numDeriv

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

This package implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
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

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

Eric Polley, Erin LeDell, Mark van der Laan
Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
arm, caret, class, e1071, earth, gam, gbm, genefilter,
ggplot2, glmnet, Hmisc, ipred, lattice, LogicReg, MASS, mda,
mlbench, nloptr, nnet, party, polspline, quadprog,
randomForest, ROCR, rpart, SIS, spls, stepPlr, sva

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")))
Implements the super learner prediction method and contains a
library of prediction algorithms to be used in the super learner.
arm, bartMachine, caret, class, e1071, earth, gam, gbm,
genefilter, ggplot2, glmnet, Hmisc, ipred, lattice, LogicReg,
MASS, mda, mlbench, nloptr, nnet, party, polspline, quadprog,
randomForest, ROCR, rpart, SIS, spls, stepPlr, sva, testthat,
xgboost (>= 0.6)
Eric Polley [aut, cre],
Erin LeDell [aut],
Chris Kennedy [aut],
Sam Lendle [ctb],
Mark van der Laan [aut, ths]