wle.lm.summaries {wle} | R Documentation |
All these functions are methods
for class wle.lm
or summary.wle.lm
.
coef.wle.lm(object, ...) formula.wle.lm(object, ...) fitted.wle.lm(object, ...) model.frame.wle.lm(formula, data, na.action, ...) summary.wle.lm(object, root="ALL", ...) summary.wle.lm.root(object, root=1, ...) print.wle.lm(x, digits = max(3, getOption("digits") - 3), ...) print.summary.wle.lm(x, digits = max(3, getOption("digits") - 3), signif.stars= getOption("show.signif.stars"), ...) print.summary.wle.lm.root(x, digits = max(3, getOption("digits") - 3), signif.stars= getOption("show.signif.stars"), ...)
object |
an object of class wle.lm . |
x |
an object of class wle.lm or summary.wle.lm . |
formula |
a model formula |
data |
data.frame , list, environment or object coercible to data.frame containing the variables in formula . |
na.action |
how NA s are treated. The default is first, any na.action attribute of data , second a na.action setting of options , and third na.fail if that is unset. The ``factory-fresh'' default is na.omit . |
root |
the root to be printed, in summary.wle.lm it could be "ALL", all the roots are printed, or a vector of integers. |
print.summary.wle.lm
and print.summary.wle.lm.root
tries formatting for each root the coefficients, standard errors, etc. and additionally gives ``significance stars'' if signif.stars
is TRUE
.
The function summary.wle.lm
(the summary.wle.lm.root
do the same for just one selected root) computes and returns, for each selected root, a list of summary statistics of the fitted linear model given in object
, using the components (list elements) "call"
and "terms"
from its argument, plus
residuals |
the weighted residuals, the usual residuals rescaled by the square root of the weights given by wle.lm . |
coefficients |
a p x 4 matrix with columns for the estimated coefficient, its standard error, weighted-t-statistic and corresponding (two-sided) p-value. |
sigma |
the square root of the estimated variance of the random error. |
df |
degrees of freedom, a 3-vector (p, sum{weights} - p, p*). |
fstatistic |
a 3-vector with the value of the weighted-F-statistic with its numerator and denominator degrees of freedom. |
r.squared |
R^2, the ``fraction of variance explained by the model''. |
adj.r.squared |
the above R^2 statistic ``adjusted'', penalizing for higher p. |
root |
the label of the root reported. |
Claudio Agostinelli
wle.lm
a function for estimating linear models with normal distribution error and normal kernel, plot.wle.lm
for plot method.
library(wle) # You can find this data set in: # Hawkins, D.M., Bradu, D., and Kass, G.V. (1984). # Location of several outliers in multiple regression data using # elemental sets. Technometrics, 26, 197-208. # data(artificial) result <- wle.lm(y.artificial~x.artificial,boot=40,group=6,num.sol=3) #summary only for the first root summary(result,root=1) #summary for all the roots summary(result,root="ALL")