R: Calculate contrasts from multivariable predictions

get.contr {gstat} | R Documentation

## Calculate contrasts from multivariable predictions

### Description

Given multivariable predictions and prediction (co)variances, calculate contrasts and their (co)variance

### Usage

     get.contr(data, gstat.object, X, ids = names(gstat.object$data))

### Arguments

`data` | data frame, output of predict
`gstat.object` | object of class `gstat`, used to extract ids; may be missing if `ids` is used
`X` | contrast vector or matrix; the number of variables in `gstat.object` should equal the number of elements in `X` if `X` is a vector, or the number of rows in `X` if `X` is a matrix.
`ids` | character vector with (selection of) id names, present in data

### Details

From data, we can extract the n x 1 vector with multivariable predictions, say $y$, and its n x n covariance matrix $V$. Given a contrast matrix in $X$, this function computes the contrast vector $C=X'y$ and its variance $Var(C)=X'V X$.

### Value

a data frame containing for each row in `data` the generalized least squares estimates (named beta.1, beta.2, ...), their variances (named var.beta.1, var.beta.2, ...) and covariances (named cov.beta.1.2, cov.beta.1.3, ...)

### Author(s)

Edzer Pebesma

### References

http://www.gstat.org/

### See Also

predict

[Package gstat version 2.0-3 Index]