rstandard.zlm: Standardized Residuals from Ordinary or Robust Linear fits with Complex Variables

Description

Generates a vector of residuals from the given complex linear model that are normalized to have unit variance. Similar to stats::rstandard, which this function calls if given numeric input.

Usage

# S3 method for zlm
rstandard(model, lever = zhatvalues(model), ...)

Value

A complex vector of length equal to that of the residuals of model. Numeric for numeric input.

Arguments

model: An object of class "zlm", "rzlm", "lm", or "rlm". Can be complex or numeric.
lever: A list of leverage scores with the same length as model$residuals. By default zhatvalues is called on model.
...: Other parameters. Only used if model is numeric; in which case they are passed to stats::rstandard.

Details

The standardized residuals are calculated as,
$r^{'} = r / (s \sqrt{1 - l e v e r})$
Where $r$ is the residual vector and $s$ is the residual standard error for "zlm" objects or the robust scale estimate for "rzlm" objects.

Examples

Run this code

set.seed(4242)
n <- 8
slop <- complex(real = 4.23, imaginary = 2.323)
interc <- complex(real = 1.4, imaginary = 1.804)
e <- complex(real=rnorm(n)/6, imaginary=rnorm(n)/6)
xx <- complex(real= rnorm(n), imaginary= rnorm(n))
tframe <- data.frame(x = xx, y= slop*xx + interc + e)
fit <- lm(y ~ x, data = tframe, weights = rep(1,n))
rstandard(fit)

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