API for nsgp
Non-Stationary Gaussian Process Regression

Global functions
RBF Source code
RBF.blocks Source code
RBF.deriv Source code
RBF.deriv2 Source code
bexp Source code
drawSamples Source code
drawShading Source code
gaussiankernel Source code
ggplotcolors Source code
gpr1sample Man page Source code
gpr2sample Man page Source code
gpr_posterior Man page Source code
gpsimple Man page Source code
gradientfuncs Source code
handlenoise Source code
learnnoise Source code
normkernel Source code
nsRBF Source code
nsRBF.blocks Source code
nsRBF.deriv Source code
nsRBF.deriv2 Source code
nsgp Man page
nsgp-package Man page
nterpolate Source code
optim_dyn Source code
optim_dyn_gradients Source code
optim_exp Source code
optim_exp_gradients Source code
optim_exp_sample Source code
optim_exp_sample_gradients Source code
optim_fit_dyn Source code
optim_fit_dyn_gradients Source code
optim_stat Source code
optim_stat_gradients Source code
optimize_dynamic Source code
optimize_expected Source code
optimize_static Source code
plot.gp Man page Source code
plot.gppack Man page Source code
plot.gpsimple Man page Source code
plotdistr Source code
plotls Source code
print.gp Man page Source code
print.gppack Man page Source code
print.gpsimple Man page Source code
randparams Source code
sample Source code Source code
sample.gp Source code
sample.gpsimple Source code
sigmalower Source code Source code
sigmalower.gp Source code
sigmalower.gpsimple Source code
sigmaupper Source code Source code
sigmaupper.gp Source code
sigmaupper.gpsimple Source code
simgp_clust Source code
simulategp Man page Source code
simulategp.perturbed Man page Source code
summary.gp Man page Source code
summary.gppack Man page Source code
summary.gpsimple Man page Source code
toydata Man page
toygps Man page
triangular Source code
uniform Source code
nsgp documentation built on May 29, 2017, 11:47 p.m.