R: Fields internal and secondary functions

fields internal {fields} | R Documentation

## Fields internal and secondary functions

### Description

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

### Usage

    ## S3 method for class 'spatialDesign'
    x[...]

    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)

    ## S3 method for class 'spatialDesign'
    plot(x,...)

    ## S3 method for class 'interp.surface'
    predict(object, loc,...)

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

    ## S3 method for class 'spatialDesign'
     print(x,...)
    ## S3 method for class 'sreg'
    print(x, ...)
    ## S3 method for class 'summary.Krig'
     print(x, ...)
    ## S3 method for class 'summary.spatialProcess'
     print(x, ...)
    ## S3 method for class 'summarySpatialDesign'
     print(x, digits = 4,...)
    ## S3 method for class 'summary.sreg'
     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)
    ## 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)

    quickPrint(obj, max.values = 10)

    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 'qsreg'
     summary(object, ...)
    ## S3 method for class 'spatialDesign'
     summary(object, digits = 4, ...)
    ## S3 method for class 'sreg'
     summary(object, digits = 4, ...)

    surface(object , ...)
    ## Default S3 method:
     surface(object, ...)

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

    MLESpatialProcess.fast(x, y, lambda.start=.5, theta.start = NULL,
      cov.function = "stationary.cov",
      cov.args = list(Covariance = "Matern", smoothness = 1),
      Distance = "rdist", verbose=FALSE, optim.args=NULL, ...)

[Package fields version 9.6.1 Index]