Displaying 4 results from an estimated 4 matches for "summary2".
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2008 Mar 21
0
How to Package Extra Results to summary.lm
Dear R users,
I came up with some simple functions to give me the standard betas and
tolerance values from a predefined lm() model. I have been trying to
insert the results from these functions into the coefficients matrix in
a modified summary.lm function that I'm calling summary2 (I'd never edit
the summary.lm function directly!!). I managed to get the results
inserted into the output, but a few things have changed: 1) Now instead
of the Pr(>|t|) column being the only one to ever be expressed in
scientific notation, the other columns (except for the new 'Tol...
2007 Jul 13
2
Suggestion to extend aggregate() to return multiple and/or named values
...h=50) #another factor
Ind=list(A=A,B=B) #the factor list
aggregate(z,Ind,mean) #show the means of each cell
agg(z,Ind,mean) #should be identical to aggregate
aggregate(z,Ind,summary) #returns an error
agg(z,Ind,summary) #returns named columns
#Make a function that returns multiple unnamed values
summary2=function(x){
s=summary(x)
names(s)=NULL
return(s)
}
agg(z,Ind,summary2) #returns multiple columns, default names
--
Mike Lawrence
Graduate Student, Department of Psychology, Dalhousie University
Website: http://memetic.ca
Public calendar: http://icalx.com/public/informavore/Public
"The...
2008 Dec 07
5
How to force aggregate to exclude NA ?
The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle.
> set.seed(143)
> m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T))
> m
A B C D
1 E I 1 NA
2 A C NA NA
3 D I NA 3
4 C I
2010 Mar 27
1
R runs in a usual way, but simulations are not performed
...edure$beta_egls; beta_covmat_new =
krprocedure$beta_covmat_new
beta_covmat_old = krprocedure$beta_covmat_old; beta_egls =
krprocedure$beta_egls
if (krprocedure$model == "ADD") {
summary1 <-
cbind(data.frame("Parameter"=c("Estimates")),BETA=t(as.vector(beta_egls)))
summary2 <- cbind(BETA=beta_covmat_old)
cat("**Parameter estimates of the additive heteroskedasticity
model**\n")
cat("-----------------------------------------------------------------------------\n")
print(summary1,row.names=FALSE)
cat("-----------------------------------------...