# Covariance Matrix for a Covariance Kernel Object Covariance matrix for a covariance kernel object. methods ```r ## S4 method for signature 'covMan' covMat(object, X, Xnew, compGrad = hasGrad(object), checkNames = NULL, index = 1L, ...) ## S4 method for signature 'covTS' covMat(object, X, Xnew, compGrad = FALSE, checkNames = TRUE, index = 1L, ...) ``` ## Arguments - `object`: An object with S4 class corresponding to a covariance kernel. - `X`: The matrix (or data.frame) of design points, with $n$ rows and $d$ cols where $n$ is the number of spatial points and $d$ is the 'spatial' dimension. - `Xnew`: An optional new matrix of spatial design points. If missing, the same matrix is used: `Xnew = X`. - `compGrad`: Logical. If `TRUE` a derivative with respect to a parameter will be computed and returned as an attribute of the result. For the `covMan` class, this is possible only when the gradient of the kernel is computed and returned as a `"gradient"` attribute of the result. - `checkNames`: Logical. If `TRUE` (default), check the compatibility of `X` with `object`, see `checkX`. - `index`: Integer giving the index of the derivation parameter in the official order. Ignored if `compGrad = FALSE`. - `...`: not used yet. ## Details The covariance matrix is computed in a C program using the `.Call` interface. The R kernel function is evaluated within the C code using `eval`. ## Returns A $(n_1, n_2)$ matrix with general element c("$C[i, j] = K(X1[i,\n$", "$ ], X2[j, ], \\theta)$") where c("$K(x1, x2,\n$", "$ \\theta)$") is the covariance kernel function. ## Author(s) Y. Deville, O. Roustant, D. Ginsbourger, N. Durrande. ## Note The value of the parameter $\theta$ can be extracted from the object with the `coef` method. ## See Also `coef` method ## Examples ```r myCov <- covTS(inputs = c("Temp", "Humid", "Press"), kernel = "k1PowExp", dep = c(range = "cst", shape = "cst"), value = c(shape = 1.8, range = 1.1)) n <- 100; X <- matrix(runif(n*3), nrow = n, ncol = 3) try(C1 <- covMat(myCov, X)) ## bad colnames colnames(X) <- inputNames(myCov) C2 <- covMat(myCov, X) Xnew <- matrix(runif(n * 3), nrow = n, ncol = 3) colnames(Xnew) <- inputNames(myCov) C2 <- covMat(myCov, X, Xnew) ## check with the same matrix in 'X' and 'Xnew' CMM <- covMat(myCov, X, X) CM <- covMat(myCov, X) max(abs(CM - CMM)) ```

covMat-methods function