Hi, Bruce:
I'm overwhelmed. Questioners seem to get quicker, more informative
responses to questions that are short, well written and easily and
quickly understood, and preferably include a toy example that someone
else can run quickly to reproduce the problem and to evaluate
alternative solutions.
I see you are using "source" and would like to get more output.
Did
you check "?source"? This function in R has arguments
"echo" and
"verbose", which may produce what you want. If you've already
tried
that, then the problem may be output buffering, and I don't know how to
modify that parameter. A search of "www.r-project.org" -> search
-> "R
Site Search" might help. Or ask a question focused specifically on
that, giving also which version of R you are using under which operating
system.
I rarely use "source". More often, I have R commands in another
file
and copy and paste into R the commands I want to run. That makes it
easier for me to isolate errors, etc.
This does not address all your questions, but it's a start.
Hope this helps.
spencer graves
Bruce Moore wrote:> I'm writing a program to perform linear regressions to
> estimate the number of bank teller transactions per
> hour of various types based upon day of week, time of
> day, week of month and several prices. I've got about
> 25,000 records in my dataset, 85 columns of
> transaction counts (used 1 at a time), about 50
> columns of binary indicators (day, week, pay period,
> hour, branch), and a half dozen real valued prices.
>
> My program hangs on some regressions as I add
> interactions, probably due to logic problems in my
> code or collinearity problems in the data.
>
> 1) I'm running my program via the source() command.
> It appears that source() does not print any messages
> until it completes.
>
> ---->Is there a way to get diagnostic messages to
> print immediately rather than when the source()
> command has completed?
>
> 2) I'm fairly certain that I've got some collinearity
> in the data set and the interactions. I've found an
> append (Ott Toomet 5/30/2003) that talks about a
> procedure to find collinearity problems using
> model.matrix() to generate the dataset with
> interactions and kappa() to determine the condition
> number of the matrix.
>
> ---->Is there a more automated way to find collinear
> variables?
>
> 3) Is there a way to get lm() and/or step() or some
> other package to give a model with only coefficients
> that are significant at a particular level?
>
> 4) Is there a way to suppress display of a password
> when using the RODBC odbcConnect() function, or to get
> the function to prompt for a password?
>
> 5) What is the practical size limit on the number of
> terms in model? I know that I won't be able to
> consider all interactions, but would like to have some
> idea when to give up and go with what I've got.
>
>
>
> ====> Bruce Moore
>
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