MISE.envelope | R Documentation |
Compute the mean integrated squared error, or integrated squared bias, or integrated variance, of the simulated function estimates in an envelope object.
ISB.envelope(object, theo, domain, dimension=2)
IV.envelope(object, domain, dimension=2)
MISE.envelope(object, theo, domain, dimension=2)
object |
Object of class |
theo |
Function in the R language that evaluates the true (theoretically expected) value of the spatial summary function. |
domain |
Numeric vector of length 2 specifying the limits of the domain of integration for the integrated squared error. |
dimension |
Integer (either 1 or 2) specifying whether to calculate the one-dimensional or two-dimensional integral of squared error. |
The first argument should be an object of class "envelope"
and should contain the simulated function estimates (i.e. it should
have been computed using envelope
with savefuns=TRUE
).
MISE.envelope
computes the mean integrated squared error.
ISB.envelope
computes the integrated squared bias.
IV.envelope
computes the integrated sample variance.
The simulated function estimates are extracted from object
and their deviation from the true function theo
is computed pointwise. The squared deviations are integrated over the
interval specified by domain
, giving one value of integrated
squared error for each simulated function estimate. Then
MISE.envelope
returns the average of these values, that is,
the estimated mean squared error. Similarly for the other computations.
A single numeric value.
, \martinH and \tilman.
bias.envelope
,
ISE.envelope
.
E <- envelope(cells, Kest, nsim=20, savefuns=TRUE)
theoK <- function(r) { pi * r^2 }
dom <- c(0, 0.1)
MISE.envelope(E, theoK, dom)
ISB.envelope(E, theoK, dom)
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