Tests if the given function supports the given argument. Commonly used in fields code for determining if a covariance function supports precomputation of the distance matrix and evaluation of the covariance matrix over only the upper triangle.
Here are some technical hints for assembling multiple plots with common legends or axes and setting the graphics parameters to make more readable figures. Also we an index to the defaultcolors in R graphics and setting their definitions in LaTeX. All these hints use the standard graphics environment.
Fits a surface to irregularly spaced data. The Kriging model assumes that the unknown function is a realization of a Gaussian random spatial processes. The assumed model is additive Y = P(x) + Z(X) + e, where P is a low order polynomial and Z is a mean zero, Gaussian stochastic process with a covariance that is unknown up to a scale constant. The main advantages of this function are the flexibility in specifying the covariance as an R language function and also the supporting functions plot, predict, predictSE, surface for subsequent analysis. Krig also supports a correlation model where the mean and marginal variances are supplied.
The Engines:
(Package: fields) :
Basic linear algebra utilities and other
These are internal functions to Krig that compute the basic matrix decompositions or solve the linear systems needed to evaluate the Krig/Tps estimate. Others listed below do some simple housekeeping and formatting. Typically they are called from within Krig but can also be used directly if passed a Krig object list.
Discretizes a set of 2-d locations to a grid and produces a image object with the z values in the right cells. For cells with more than one Z value the average is used.
For a fixed smoothness (shape) parameter these functions provide different ways of estimating and testing restricted and profile likehiloods for the Martern covariance parameters. MLE.Matern is a simple function that finds the restricted maximum likelihood (REML) estimates of the sill, nugget and range parameters (rho, sigma2 and theta) of the Matern covariance functions. The remaining functions are primarily for testing.
compactToMat transforms a matrix from compact, vector form to a standard matrix. Only symmetric matrices can be stored in this form, since a compact matrix is stored as a vector with elements representing the upper triangle of the matrix. This function assumes the vector does not contain diagonal elements of the matrix.
providing 
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