Krig.df.to.lambda(df, D, guess = 1, tol = 1e-05)
Krig.fdf (llam, info)
Krig.fgcv (lam, obj)
Krig.fgcv.model (lam, obj)
Krig.fgcv.one (lam, obj)
Krig.flplike (lambda, obj)
Krig.fs2hat (lam, obj)
Krig.ftrace (lam, D)
Krig.parameters (obj, mle.calc=obj$mle.calc)
Krig.updateY (out, Y, verbose = FALSE, yM=NA)
Krig.which.lambda(out)
Krig.ynew (out, y=NULL, yM=NULL )
bisection.search (x1, x2, f, tol = 1e-07, niter = 25, f.extra = NA, upcross.level = 0)
cat.matrix (mat, digits = 8)
cat.to.list (x, a)
ceiling2 (m)
describe (x)
double.exp(x)
dyadic.2check( m,n,cut.p=2)
dyadic.check( n,cut.p=2)
Exp.earth.cov (x1, x2, theta = 1)
fast.1way (lev, y, w = rep(1, length(y)))
find.upcross (fun, fun.info, upcross.level = 0, guess = 1, tol =
1e-05)
gauss.cov (...)
golden.section.search (ax, bx, cx, f, niter = 25, f.extra = NA, tol = 1e-05, gridx=NA)
imagePlotInfo (...,breaks, nlevel)
imageplot.info(...)
imageplot.setup(x, add=FALSE, legend.shrink = 0.9, legend.width = 1,
horizontal = FALSE, legend.mar=NULL, bigplot = NULL, smallplot = NULL,...)
makeSimulationGrid(mKrigObject, predictionPoints, nx, ny, nxSimulation, nySimulation, gridRefinement, gridExpansion)
makeSimulationGrid2 (fastTpsObject, predictionPointsList, gridRefinement, gridExpansion)
minimax.crit (obj, des = TRUE, R)
"plot"(x,...)
"predict"(object, loc,...)
"predict"(object, ...)
"predict"(object, ...)
"print" (x,...)
"print"(x, ...)
"print" (x, ...)
"print" (x, ...)
"print" (x, digits = 4,...)
"print" (x, ...)
printGCVWarnings( Table, method = "all")
makePredictionPoints(mKrigObject, nx, ny, predictionPointsList)
multWendlandGrid( grid.list,center, delta, coef, xy = c(1, 2))
qr.q2ty (qr, y)
qr.yq2 (qr, y)
"plot"(x, pch = "*", main = NA,...)
"predict"(object, x, derivative = 0, model = object$ind.cv.ps,...)
"print" (x, ...)
qsreg.fit (x, y, lam, maxit = 50, maxit.cv = 10, tol = 1e-04, offset = 0, sc = sqrt(var(y)) * 1e-07, alpha = 0.5, wt = rep(1, length(x)), cost = 1)
qsreg.psi( r,alpha=.5,C=1)
qsreg.rho( r,alpha=.5,C=1)
qsreg.trace(x, y, lam, maxit = 50, maxit.cv = 10, tol = 1e-04, offset = 0, sc = sqrt(var(y)) * 1e-07, alpha = 0.5, wt = rep(1, length(x)), cost = 1)
qsreg.rho.OLD(r, alpha = 0.5, C = 1)
qsreg.psi.OLD(r, alpha = 0.5, C = 1)
quickPrint(obj, max.values = 10)
"summary" (object, ...)
radbas.constant (m, d)
sreg.df.to.lambda (df, x, wt, guess = 1, tol = 1e-05)
sreg.fdf (h, info)
sreg.fgcv (lam, obj)
sreg.fgcv.model (lam, obj)
sreg.fgcv.one (lam, obj)
sreg.fit (lam, obj, verbose=FALSE)
sreg.fs2hat (lam, obj)
sreg.trace (h, info)
summaryGCV.Krig(object, lambda, cost = 1, verbose = FALSE, offset = 0, y = NULL, ...)
summaryGCV.sreg (object, lambda, cost = 1, nstep.cv = 20, offset = 0, verbose = TRUE,...)
"summary" (object, digits = 4, ...)
"summary" (object, digits = 4, ...)
surface(object , ...)
"surface" (object, ...)
unscale (x, x.center, x.scale)
MLESpatialProcess.fast(x, y, lambda.start = NULL, theta.start = NULL, cov.function = "stationary.cov", cov.args = list(Covariance = "Matern", smoothness = 1), relative.tolerance = 0.001, Distance = "rdist", verbose = FALSE, ...)