search for: keithc

...list, How is the tolerance for a model parameter in an lm() call extracted? I did not see a solution in the documentation for lm(), or predict(), nor in the archives using 'tolerance' as the search string. I also checked into the nlme package, though nothing popped out at me. Sincerely, KeithC.

...type for $KSesnMain/MenuTest in: MenuType(menu) 3: Unrecognized menu type for $KSesnMain/MenuTest in: MenuType(menu) 4: Unrecognized menu type for $KSesnMain/MenuTest in: MenuType(menu) <menu.txt - in RHOME> $KSesnMain |$MenuTest ||Objects ~~ ls() ||- ||Path ~~ search() Please Advise, KeithC.

...umn and set C1 to corresponding value of Cat. for(i in 1:length(C1)){ if(Cat[i]=='a') C1[i]=-1 else C1[i]=1 } C1 [1] -1 -1 -1 1 1 1 -1 -1 1 Cat [1] "a" "a" "a" "b" "b" "b" "a" "a" "b" Sincerely, KeithC. Psych Undergrad, CU Boulder (US) RE McNair Scholar

...s x2<-fft(fx, inverse=T) plot(Re(x2)) ## not quite what I intended . Which, although I get some fantastic looking plots, isn't quite what I anticipated. How do I apply a function or filter in the frequency domain, then inverse transform to the scale of my original time series? Sincerely, KeithC. Psych Undergrad, CU Boulder RE McNair Scholar [U.S] [[alternative HTML version deleted]]

...obably help). I have not had the chance to test routines on a Mac yet, so I have no idea what to expect. Is this tract I took with winMenuAdd() & related [{utils} windows build] an appropriate route to take wrt the Mac build of R, or would I be better off using another package? Please advise, KeithC.

...ame "if previously setup". What kind of setup is needed outside of R, if any? 4- what steps are needed in R to then connect to a file and import a subset based on a query? 5- Do I then use standard R routines (e.g. write()) to export as a DB, or an RDB/XML specific function? Sincerely, KeithC. [U.S] 1/k^c

..."mean". > dew<-extend.series(c,method="mean",length="powerof2", j=log(length(c),2)%/%1) > > length(dew) [1] 128 > Has this come up in anyone else's experience? If so, what's the workaround so that I can use "zero" as a method? Rgds, KeithC.

Hi, is there a way to take a dataset and extract numeric columns and create interaction columns from it automatically? For e.g. there are 5 columns of data: A,B,C,D,E. CDE are numeric. Can someone provide code to automatically create more columns such as: 1) C*D, C*E, C*D*E, (C+E)/(D+.01 (to avoid divide by zero), (D+E)/(C+.01 (to avoid divide by zero), (C+D)/(E+.01 (to avoid

...o me yet). Conversely, I got a lot farther, a lot faster, using Lattice than I did using plot or ts.plot. In addition to a much shorter list of attributes that don't make sense to me yet than otherwise, I have been really tickled with the Lattice package. Thanks in advance for your feedback. KeithC.

...on would be evident in the stated conventions. Thus, I should hope that if spec.pgram() is normed too the SS amplitude of the discrete function, someone could communicate why it isn't exactly the SS amplitude, or conversely what the norming convention is. Thank you very much for your feedback, KeithC. - an aspiring signal analysis guru & honorary enginerd chamberk at colorado.edu Psych Undergrad, CU Boulder RE McNair Scholar "Perhaps we're the reason they call it 'psycho'physics..."

...s human seems to have made meaning out of terms differently than what those who wrote the documentation seem to have intended. Only, I do not know where the documentation or my understanding may have been missled (R docs, Numerical Recipes, or any other source I looked at since I started). Cheers, KeithC. First, please look up `too' in your dictionary. Second, please study the references on the help page, which give the details. That is what references are for! The references will also answer your question about the reference distribution. The help page does not say it is `normalized'...

Hello, I am trying to learn how to perform Multiple Regression Analysis in R. I decided to take a simple example given in this PDF: http://www.utdallas.edu/~herve/abdi-prc-pretty.pdf I created a small CSV called, students.csv that contains the following data: s1 14 4 1 s2 23 4 2 s3 30 7 2 s4 50 7 4 s5 39 10 3 s6 67 10 6 Col headers: Student id, Memory span(Y), age(X1), speech rate(X2) Now

As a newbie to R I have the following question. I would like to compare values in a time series with values of the same series x observations ago. In gretl this is simply done like so: In R, I seem not to get it working. I have tried lag(data,-x) to obtain the lagged time series which produces the following error message: Error in attr(x, "tsp") <- c(1, NROW(x), 1) :

...in your message may have become garbled when it was stripped of all of its HTML information. If the code was formatted in a readable way when you sent the message, then that's what happened. If that is the case try composing your message in plain text to begin with. I hope this helps. Rgds, KeithC.

...alculate the shape of the spectral density for linear models using Fourier estimates (e.g. terms for a linear model derived from the frequency domain)? I have data with a long memory process but do not want to destroy it by taking n-differences for a suitable corAR, or corARIMA object. Thank you, KeithC.

...I determine what means comparisons are taking place a-priori. Does it matter for e.g. 'contr.SUM' that the data are stacked, and does 'contr.SUM' allow me to set the contrasts efficiently even if the data are unballanced? Is there an alternative in R I should consider? Sincerely, KeithC. Psych Undergrad, CU Boulder (US)

...http://rwiki.sciviews.org/doku.php?id=large_scale_data. This is a massive topic of interest to many. I could use some help filling in the content so that this can develop into a powerful resource for the r-community. I hope you like it, and I hope you are willing to help make it better. Sincerely, KeithC.

hello, i'd like to evaluate the 2 factors (f1 with 4, f2 with 2 levels) and its interactions in my model for writing up a summary table with likelihood-ratio tests for publication purpose. now i'm unsure about which terms of my model may be dropped from the full model and which not. mfull<-lme(resp~f1*f2,random=...) m1<-lme(resp~f1+f2,..) m2<-lme(resp~f1,..)

Rhelpers: I'd like to modify this RSQLite statement: rs_stations<-dbSendQuery(con_stations, "select * from stations") so that stations is actually an R variable, e.g.: stations=c("stationA","stationB") How would I modify the above statement to query from stations[[1]] (aka "stationA")? --j

hi, I have a list L having more than 14000 Elements, each of these contains an array of about length 1200. > L[[1]][26:30] # e.g. print 5 entries of first element of L [1] 0.0000000 6.7982652 114.4737184 89.7328239 3.2001664 Furthermore I get two arrays A and B of same length as input. A<-c(4,7,9,34,463,788) B<-c(50,67,87,361,45,89) I would like to extract (or print or save)