Description Usage Arguments Details Author(s) See Also Examples
This page documents the methods fixef
,
fixed.effects
, model.frame
,
model.matrix
, nobs
, print
, ranef
,
random.effects
, resid
, residuals
, rstandard
,
rstudent
, summary
and vcov
for the
class georob
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | ## S3 method for class 'georob'
fixef(object, ...)
## S3 method for class 'georob'
fixed.effects(object, ...)
## S3 method for class 'georob'
model.frame(formula, ...)
## S3 method for class 'georob'
model.matrix(object, ...)
## S3 method for class 'georob'
nobs(object, ...)
## S3 method for class 'georob'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'georob'
ranef(object, standard = FALSE, ...)
## S3 method for class 'georob'
random.effects(object, standard = FALSE, ...)
## S3 method for class 'georob'
resid(object,
type = c("working", "response", "deviance", "pearson", "partial" ),
terms = NULL,
level = 1, ... )
## S3 method for class 'georob'
residuals(object,
type = c("working", "response", "deviance", "pearson", "partial" ),
terms = NULL,
level = 1, ... )
## S3 method for class 'georob'
rstandard(model, level = 1, ...)
## S3 method for class 'georob'
rstudent(model, ...)
## S3 method for class 'georob'
summary(object, correlation = FALSE, signif = 0.95, ...)
## S3 method for class 'georob'
vcov(object, ...)
|
object, model, x |
an object of class |
formula |
a model |
correlation |
logical controlling whether the correlation matrix of
the estimated regression coefficients and of the fitted variogram
parameters (only for non-robust fits) is computed (default |
digits |
positive integer indicating the number of decimal digits to print. |
level |
an optional integer giving the level for extracting the
residuals from |
signif |
confidence level for computing confidence intervals for
variogram parameters (default |
standard |
logical controlling whether the spatial random effects
B should be standardized (default
|
type |
character keyword indicating the type of residuals to compute, see
|
terms |
If |
... |
additional arguments passed to methods. |
The methods model.frame
, model.matrix
and nobs
extract the model frame, model matrix and the number of observations, see
help pages of respective generic functions.
The methods residuals
(and resid
) extract either the
estimated independent errors
hatε(s)
or the sum of the latter quantities and the spatial random effects
hatB(s).
rstandard
does the same but standardizes the residuals to unit
variance. ranef
(random.effects
) extracts the spatial
random effects with the option to standardize them as well, and
fixef
(fixed.effects
) extracts the fitted regression
coefficients, which may of course also be obtained by coef
.
Besides, the default methods of the generic functions
coef
, confint
,
df.residual
, fitted
,
formula
, termplot
and
update
can be used for objects of class
georob
.
Andreas Papritz andreas.papritz@env.ethz.ch
georobIntro
for a description of the model and a brief summary of the algorithms;
georob
for (robust) fitting of spatial linear models;
georobModelBuilding
for stepwise building models of class georob
;
georobObject
for a description of the class georob
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ## Not run:
data(meuse)
## Gaussian REML fit
r.logzn.reml <- georob(log(zinc) ~ sqrt(dist), data = meuse, locations = ~ x + y,
variogram.model = "exponential",
param = c( variance = 0.15, nugget = 0.05, scale = 200 ),
tuning.psi = 1000,
control = georob.control(cov.bhat = TRUE, cov.ehat.p.bhat = TRUE))
summary(r.logzn.reml, correlation = TRUE)
## robust REML fit
r.logzn.rob <- update(r.logzn.reml, tuning.psi = 1)
summary(r.logzn.rob, correlation = TRUE)
## residual diagnostics
old.par <- par(mfrow = c(2,3))
plot(fitted(r.logzn.reml), rstandard(r.logzn.reml))
abline(h = 0, lty = "dotted")
qqnorm(rstandard(r.logzn.reml))
abline(0, 1)
qqnorm(ranef(r.logzn.reml, standard = TRUE))
abline(0, 1)
plot(fitted(r.logzn.rob), rstandard(r.logzn.rob))
abline(h = 0, lty = "dotted")
qqnorm(rstandard(r.logzn.rob))
abline(0, 1)
qqnorm(ranef(r.logzn.rob, standard = TRUE))
abline(0, 1)
par(old.par)
## End(Not run)
|
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