Calculate contrasts from multivariable predictions

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 $n \times 1$ vector with multivariable predictions, say $y$, and its $n \times n$ 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, ...)

References

http://www.gstat.org/

Author

Edzer Pebesma