Displaying 20 results from an estimated 900 matches similar to: "Cook's Distance in GLM (PR#9316)"
2004 Mar 23
1
influence.measures, cooks.distance, and glm
Dear list,
I've noticed that influence.measures and cooks.distance gives different
results for non-gaussian GLMs. For example, using R-1.9.0 alpha
(2003-03-17) under Windows:
> ## Dobson (1990) Page 93: Randomized Controlled Trial :
> counts <- c(18,17,15,20,10,20,25,13,12)
> outcome <- gl(3,1,9)
> treatment <- gl(3,3)
> glm.D93 <- glm(counts ~ outcome +
2008 May 09
0
Incorrect fix for PR#9316: Cook's Distance & plot.lm
Bug PR#9316 noted an inconsistency between the Cook's distance contours
on plot.lm(x, which = 5) and the values given by cooks.distance(x) -- as
shown in plot.lm(x, which = 4) -- for glms:
http://bugs.r-project.org/cgi-bin/R/Analyses-fixed?id=9316;user=guest;selectid=9316
The suggested fix was to modify the contour levels by a dispersion
factor, implemented as follows:
dispersion <-
2005 Feb 02
1
anova.glm (PR#7624)
There may be a bug in the anova.glm function.
deathstar[32] R
R : Copyright 2004, The R Foundation for Statistical Computing
Version 2.0.1 (2004-11-15), ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project
2005 Feb 11
1
cook's distance in weighted regression
I have a puzzle as to how R is computing Cook's distance in weighted linear
regression.
In
this case cook's distance should be given not as in OLS case by
h_ii*r_i^2/(1-hii)^2 divided by k*s^2 (1)
(where r is plain unadjusted residual, k is number of parameters in model,
etc. )
but rather by
w_ii*h_ii*r_i^2/(1-hii)^2 divided by k*s^2,
2013 May 29
1
quick question about glm() example
I don't have a copy of Dobson (1990) from which the glm.D93 example is
taken in example("glm"), but I'm strongly suspecting that these are
made-up data rather than real data; the means of the responses within
each treatment are _identical_ (equal to 16 2/3), so two of the
parameters are estimated as being zero (within machine tolerance). (At
this moment I don't understand
2013 Mar 12
1
Cook's distance
Dear useRs,
I have some trouble with the calculation of Cook's distance in R.
The formula for Cook's distance can be found for example here:
http://en.wikipedia.org/wiki/Cook%27s_distance
I tried to apply it in R:
> y <- (1:400)^2
> x <- 1:100
> lm(y~x) -> linmod # just for the sake of a simple example
>
2013 Feb 18
1
nobs() with glm(family="poisson")
Hi!
The nobs() method for glm objects always returns the number of cases
with non-null weights in the data, which does not correspond to the
number of observations for Poisson regression/log-linear models, i.e.
when family="poisson" or family="quasipoisson".
This sounds dangerous since nobs() is, as the documentation states,
primarily aimed at computing the Bayesian
2012 Jan 12
1
posting for r-help
Hi there
I have a post I would like to put on the "95% confidence intercal with glm"
thread. Thank-you so much!
I am wondering first of all if anyone knows how to calculate confidence
intervals for a GLMM? I use the lme4 library.
Also, I am wondering how to predict a model mean and confidence intervals for a
particular independent variable?
For example in the following example:
2005 Apr 06
2
make error in R devel
Dear list,
I just hit an error that stopped my make && make check-devel operation
on my linux box (FC3, i686 P4 2GB RAM). Just to note that I've been
building the development branch(?) for some time and this is the first
hint of a problem.
1) updated the src tree using svn update
2) ran ../configure --with-recommended-package=no from my build directory
3) got:
R is now configured
2000 May 09
4
Dispersion in summary.glm() with binomial & poisson link
Following p.206 of "Statistical Models in S", I wish to change
the code for summary.glm() so that it estimates the dispersion
for binomial & poisson models when the parameter dispersion is
set to zero. The following changes [insertion of ||dispersion==0
at one point; and !is.null(dispersion) at another] will do the trick:
"summary.glm" <-
function(object, dispersion =
2008 May 26
1
Sweave does not respect width
Hello,
I'm learning to use Sweave, and I've run into a problem: sometimes, when
entering long lines of input and using long variable names, Sweave will not
insert linebreaks in a way that respects the width setting. This causes
undesirable overflows into the margins in the latex file. For example,
consider the following document (adapted from the GLM example):
\documentclass{article}
2011 Apr 29
1
logistic regression with glm: cooks distance and dfbetas are different compared to SPSS output
Hi there,
I have the problem, that I'm not able to reproduce the SPSS residual
statistics (dfbeta and cook's distance) with a simple binary logistic
regression model obtained in R via the glm-function.
I tried the following:
fit <- glm(y ~ x1 + x2 + x3, data, family=binomial)
cooks.distance(fit)
dfbetas(fit)
When i compare the returned values with the values that I get in SPSS,
2005 Oct 15
2
how to import such data to R?
the data file has such structure:
1992 6245 49 . . 20 1
0 0 8.739536 0 . . .
. . . . . "alabama"
. 0 .
1993 7677 58 . . 15 1
0 0
2008 May 14
0
Cook's Distance in GLM (PR#9316)
Well I suppose a warning's not going to hurt. Even in a case like the
occupationalStatus example where you know some points have been fitted
exactly, it might be useful to be reminded that the standardised
residuals for these points are then NaN and cannot be displayed. Of
course when you don't know in advance that this issue will arise, there
is even more reason to give a warning.
2012 Apr 09
2
Overall model significance for poisson GLM
Greetings,
I am running glm models for species counts using a poisson link function.
Normal summary functions for this provide summary statistics in the form of
the deviance, AIC, and p-values for individual predictors. I would like to
obtain the p-value for the overall model. So far, I have been using an
analysis of deviance table to check a model against the null model with the
intercept as
2009 Aug 19
3
Sweave output from print.summary.glm is too wide
Hi all
I am preparing a document using Sweave; a really useful tool. But I am having a problem.
Consider this toy example Sweave file:
\documentclass{article}
\begin{document}
<<echo=TRUE,results=verbatim>>=
options(width=40) # Set width to 40 characters
hide <- capture.output(example(glm)) # Create an example of the problem, but hide the output
summary(glm.D93) #
2006 Jan 29
1
extracting 'Z' value from a glm result
Hello R users
I like to extract z values for x1 and x2. I know how to extract coefficents
using model$coef
but I don't know how to extract z values for each of independent variable. I
looked around
using names(model) but I couldn't find how to extract z values.
Any help would be appreciated.
Thanks
TM
#########################################################
>summary(model)
Call:
2009 Feb 17
1
plot.lm: "Cook's distance" label can overplot point labels
The following code demonstrates an annoyance with plot.lm():
library(DAAGxtras)
x11(width=3.75, height=4)
nihills.lm <- lm(log(time) ~ log(dist) + log(climb), data = nihills)
plot(nihills.lm, which=5)
OR try the following
xy <- data.frame(x=c(3,1:5), y=c(-2, 1:5))
plot(lm(y ~ x, data=xy), which=5)
The "Cook's distance" text overplots the label for the point with the
2006 Mar 28
2
R 2.3.0 (alpha) on FreeBSD 6.1 fails make check-all
Hi Developers,
The alpha, compiles successfully, but it is failing make check-all (on
two seperate machines, both FreeBSD 6.1).
Here is the version string:
platform i386-unknown-freebsd6.1
arch i386
os freebsd6.1
system i386, freebsd6.1
status alpha
major 2
minor 3.0
year 2006
month 03
day 27
svn rev
2008 Mar 27
1
dreaded p-val for d^2 of a glm / gam
OK,
I really dread to ask that .... much more that I know some discussion about p-values and if they are relevant for regressions were already on the list. I know to get p-val of regression coefficients - this is not a problem. But unfortunately one editor of a journal where i would like to publish some results insists in giving p-values for the squared deviance i get out from different glm and