# Overall variance matrix

### Description

Calculates the maximum correlations possible consistent with the roughness parameters

### Usage

1 2 3 |

### Arguments

`A,B` |
Positive-definite matrices (roughness parameters) |

`Ainv,Binv` |
The inverses of |

`hp` |
An object of class |

`useM` |
Boolean, with default |

### 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 |

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