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fields (version 6.7.5)

fields internal: Fields internal and secondary functions

Description

Listed below are supporting functions for the major methods in fields.

Usage

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.find.gcvmin (info, lambda.grid, gcv, gcv.fun, tol, verbose =FALSE, 
give.warnings = TRUE)
Krig.find.REML (info, lambda.grid, llike, llike.fun, tol, verbose = TRUE, 
give.warnings = FALSE)
Krig.flplike (lambda, obj)
Krig.fs2hat (lam, obj) 
Krig.ftrace (lam, D) 
Krig.parameters (obj, mle.calc=obj$mle.calc)
Krig.replicates (out, verbose = FALSE) 
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) imageplot.info (...) imageplot.setup(x, add=FALSE, legend.shrink = 0.9, legend.width = 1, horizontal = FALSE, legend.mar=NULL, bigplot = NULL, smallplot = NULL,...) minimax.crit (obj, des = TRUE, R)

## S3 method for class 'spatial.design': plot(x,...) ## S3 method for class 'interp.surface': predict(object, loc,...) ## S3 method for class 'sreg': predict(object, x, derivative = 0, model = 1,...) ## S3 method for class 'spatial.design': print(x,...) ## S3 method for class 'sreg': print(x, ...) ## S3 method for class 'summary.Krig': print(x, ...)

## S3 method for class 'summary.spatial.design': print(x, digits = 4,...) ## S3 method for class 'summary.sreg': print(x, ...) qr.q2ty (qr, y) qr.yq2 (qr, y) ## S3 method for class 'qsreg': plot(x, pch = "*", main = NA,...) ## S3 method for class 'qsreg': predict(object, x, derivative = 0, model = object$ind.cv.ps,...) ## S3 method for class 'qsreg': 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)

## S3 method for class 'qsreg': 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,...)

## S3 method for class 'spatial.design': summary(object, digits = 4, ...) ## S3 method for class 'sreg': summary(object, digits = 4, ...)

surface(object , ...) ## S3 method for class 'default': surface(object, ...)

## S3 method for class 'surface': surface(object, ...)

unscale (x, x.center, x.scale)

Arguments