Displaying 3 results from an estimated 3 matches for "cookd".
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2005 Jul 28
1
conversion from SAS
...bloom=0;
w_chla=1/chla/chla;
run;
ODS listing close;
%macro sort_event(cut_off,last=0);
/*proc glm data=sort_dataset;
class year;
model logchla=year cos1 sin1 cos2 sin2 cos3 sin3
cos4 sin4 /solution;
by station;
where bloom=0;
output out=chla_res predicted=pred student=studres
cookd=cookd rstudent=rstudent u95=u95;
lsmeans year / at (cos1 sin1 cos2 sin2 cos3 sin3
cos4 sin4)=(0 0 0 0 0 0 0 0);
ODS output ParameterEstimates=parmest
LSmeans=lsmeans;
run;*/
proc glm data=sort_dataset;
class year month;
model chla=/solution;
by station;
weight w_chla;
where blo...
2009 Mar 05
2
identify() and postscript output
In the following, I'm fitting a logistic regression model, and using
car:::influencePlot. When I run the latter with
output to the screen, it calls identify() that lets me label
observations with large CookD.
However, if I use postscript() to get .eps output, identify() seems not
to be called at all. If instead, I
use dev.copy2eps() after getting output to the screen, the point labels
do not appear in the resulting .eps
graph. Why? Is there a workaround?
library(vcd)
data(Arthritis)
# define Bet...
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 +