applystnd.Hs: Standardize Spacial Covariates with Existing Object

In widals: Weighting by Inverse Distance with Adaptive Least Squares

Description

Standardize spacial covariates with respect to both the space and time dimensions

Usage

applystnd.Hs(Hs0, x)

Arguments

Hs0	Spacial covariates (of interpolation sites). An n* x p_s numeric matrix.
x	Spacial standardization object, as created by stnd.Hs.

Value

An n* x p_s matrix.

See Also

stnd.Hst.ls, applystnd.Hst.ls.

Examples

n.all <- 21
Hs.all <- cbind(1, rnorm(n.all, 1, 0.1), rnorm(n.all, -200, 21))

ndx.interp <- c(1,3,5)
ndx.support <- I(1:n.all)[ -ndx.interp ]


Hs <- Hs.all[ndx.support, , drop=FALSE]

xsns.obj <- stnd.Hs(Hs)

Hs0 <- Hs.all[ndx.interp, , drop=FALSE]

sHs0 <- applystnd.Hs(Hs0, xsns.obj)
sHs0

xsns.obj$sHs

crossprod(xsns.obj$sHs) / nrow(Hs)

crossprod(sHs0) / nrow(sHs0)


## The function is currently defined as
function (Hs0, x) 
{
    sHs0 <- t((t(Hs0) - x$h.mean)/x$h.sd)
    if (x$intercept) {
        sHs0[, 1] <- 1/sqrt(x$n)
    }
    return(sHs0)
  }

widals documentation built on Dec. 8, 2019, 1:07 a.m.