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wsqlab
GaSP:Train and Apply a Gaussian Stochastic Process Model
Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, <doi:10.1214/ss/1177012413>. Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", <doi:10.1007/0-387-28014-6_14>.
Maintained by William J. Welch. Last updated 9 months ago.
2.70 score 8 scripts
cran
CrossValidate:Classes and Methods for Cross Validation of "Class Prediction" Algorithms
Defines classes and methods to cross-validate various binary classification algorithms used for "class prediction" problems.
Maintained by Kevin R. Coombes. Last updated 6 years ago.
2.00 score