# ss: Overall variance matrix In multivator: A Multivariate Emulator

## Description

Calculates the maximum correlations possible consistent with the roughness parameters

## Usage

 ```1 2 3``` ```ss(A, B, Ainv, Binv) ss_matrix(hp,useM=TRUE) ss_matrix_simple(hp,useM=TRUE) ```

## Arguments

 `A,B` Positive-definite matrices (roughness parameters) `Ainv,Binv` The inverses of `A` and `B`; if missing, compute explicitly `hp` An object of class `mhp` `useM` Boolean, with default `TRUE` meaning to multiply (pointwise) by M and `FALSE` meaning not to (so giving the maximum correlation consistent with the roughness matrices B)

## Details

Function `ss()` calculates the maximum possible correlation between observations of two Gaussian processes at the same point (equation 24 of the vignette):

equation 24 of the vignette

Functions `ss_matrix()` and `ss_matrix_simple()` calculate the maximum covariances among the types of object specified in the `hp` argument, an object of class `mhp`. Function `ss_matrix()` is the preferred form; function `ss_matrix_simple()` is a less efficient, but more transparent, version. The two functions should return identical output.

## Value

Function `ss()` returns a scalar, `ss_matrix()` a matrix of covariances.

## Note

Thanks to Stephen Stretton for a crucial insight here

## Author(s)

Robin K. S. Hankin

## Examples

 ```1 2``` ```data(mtoys) ss_matrix(toy_mhp) ```

multivator documentation built on May 2, 2019, 6:13 a.m.