make.qcov {extRemes}

Covariate Matrix for Non-Stationary EVD Projections

Description

Create a matrix for use with pextRemes.

Usage

make.qcov(x, vals, nr = 1, ...)

is.qcov(x)

Arguments

x

make.qcov: A list object of class “fevd” as output from fevd.

is.qcov: Any R object.

vals

Either a named list whose names match the fitted model parameter names, or may be “threshold”, a matrix or a numeric vector of length equal to the size of the resulting matrix.

nr

The number of rows desired in the resulting matrix. Only if vals is a vector. If vals argument is not a vector, the code will either fail or the argument will be ignored.

...

optional arguments to matrix (e.g., byrow=TRUE, depending on the order for vals, if a vector). Only used if vals is a vector.

Details

Simply sets up a matrix of parameter coefficients to be used by pextRemes. In particular, all parameters/thresholds that are constant (i.e., do not depend on covariate values) should have columns of all ones. Paramters/threshold that vary in a non-stationary model may have whatever values are of interest.

is.qcov performs some very simple tests to determine if an object is a proper qcov matrix or not. It is possible to have a matrix that is not a proper qcov matrix, but the returned value is TRUE. It is also possible to have a valid qcov object that id not appropriate for a particular model. Mostly this is an internal function.

Value

An nr by np + 1 matrix is returned, where np is the number of parameters in the model. The last column is always “threshold” even if the model does not take a threshold (e.g., the GEV df), in which case the last column may be all NA, 0, or some other value depending on the vals argument.

Author(s)

Eric Gilleland

See Also

pextRemes, fevd, erlevd

Examples

data(PORTw)
fit <- fevd(TMX1, PORTw, location.fun=~AOindex, units="deg C")
fit

v <- cbind(rep(1,4), c(1, -1, 1, -1), rep(1,4), rep(1,4))
v <- make.qcov(fit, vals=v, nr=4)
v

# cf.
v <- make.qcov(fit, vals=list(mu1=c(1, -1, 1, -1)))
v

# Or
v <- make.qcov(fit, vals=c(rep(1,4), c(1, -1, 1, -1), rep(1,8), rep(0,4)), nr=4)
v