similar to: Why na.rm=FALSE is the default

Dear colleagues, I've been running some principal components analyses, which generate tables of loadings that I'm interested in looking at. print(f1$rot$load,cutoff=.4) is what I use, and it gives me what I want. However, I'm now interested in comparing these loadings across a few data sets. In other words, I would like R to match the loadings on rownames() and display them next

Dear colleagues, Has anybody any experience using the sem package to fit structural equation models using a fitting function other than ML? I have heard tell that OLS may provide better estimates when using standardized matrices generated from small sample sizes, so I was interested in comparing the two for a few models. However, ML appears to be hard-coded into the source for sem...but maybe

Dear Colleagues, Occasionally I deal with computer-generated (i.e., websurvey) data files that haven't quite worked correctly. When I try to read the data into R, I get something like this: Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : line 26 did not have 648 elements ...is there any way to get R to tell me how many elements line 26 *did* have? That

Hello, I'm having the following questionable behavior: > summary(m) Min. 1st Qu. Median Mean 3rd Qu. Max. 1 13000 26280 25890 38550 50910 > max(m) [1] 50912 > typeof(m) [1] "integer" > class(m) [1] "integer" ...it seems to me like max() and summary(m)[6] ought to return the same number. Am I doing something wrong? I'm

Hello, I have searched and failed for a program or script or method to conduct a power analysis for a MANOVA. My interest is a fairly simple case of 5 dependent variables and a single two-level categorical predictor (though the categories aren't balanced). If anybody happens to know of a script that will do this in R, I'd love to know of it! Otherwise, I'll see about writing one

Hello, I'm using a very large data set (n > 100,000 for 7 columns), for which I'm pretty happy dealing with pairwise-deleted correlations to populate my correlation table. E.g., a <- cor(cbind(col1, col2, col3),use="pairwise.complete.obs") ...however, I am interested in the number of cases used to compute each cell of the correlation table. I am unable to find such a

Dear colleagues, I run R on a few different machines, and view graphs and the like by tunnelling X through SSH to my local machine. This is useful for me because my local machine can't easily handle some of the data sets I work with. However, when an ssh connection dies, the tunnelled X session also dies, which breaks R's device connection, generating this error: > Error: X11

Dear Colleagues, Apologies for a long email to ask what I feel may be a very simple question; I figure it's better to overspecify my situation. I was asked a question, recently, by a colleague in my department about pre-aggregating variables, i.e., computing the mean of defined subsets of a data frame. Naturally, I thought of the 'by' and 'tapply' functions, as

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

Both of the following should return NA, but do not in "R version 2.11.0 Under development (unstable) (2010-03-07 r51225)" on 32-bit Windows: > mean(c(1,10,100,NA), trim=.1) Error in sort.int(x, partial = unique(c(lo, hi))) : index 4 outside bounds > mean(c(1,10,100,NA), trim=.26) [1] 55 With na.rm=TRUE they give the correct results. (mean() would be so much simpler

Dear R community I have stored the results of arrays in a list consist of J-components (say 200 components). Each component containing same no of columns but may be different no of rows. e.g [[1]] [,1] [,2] [,3] [,4] [,5] [1,] 4 0 0 0 0 [2,] 4 3 4 0 0 [3,] 4 3 4 0 0 [4,] 4 3 0 0 0 [[2]] [,1] [,2] [,3] [,4] [,5]

Hello, I frequently have to export a large quantity of data from some source (for example, a database, or a hand-written perl script) and then read it into R. This occasionally takes a lot of time; I'm usually using read.table("filename",comment.char="",quote="") to read the data once it is written to disk. However, I *know* that the program that generates

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

Hi, I'm attempting to compile R 2.7.0 on my G5, which is running OSX 10.5.2. Yes, I know there is a precompiled binary, but my experience has shown that if I hand-compile ATLAS on my machine and then link R against it when compiling, R runs faster, hence me compiling it myself. Anyway, I have this set of errors: checking X11/Intrinsic.h usability... no checking X11/Intrinsic.h presence...

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --1660387551-150661043-1249684349=:2997 Content-Type: TEXT/PLAIN; charset=iso-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE Hi Jeff, =09As mentioned in my message, I *did* replicate on another platform.=20 One platform was

Hi, I am working on establishing a Samba+LDAP server with management by the smbldap tools from idealx. Versions are Samba 3.0.14a, OpenLDAP 2.2.24, smbldap tools 0.8.8 all on Solaris 8. I'm thinking I have a problem with my perl (perhaps), version 5.8.5, as I keep getting "Broken pipe" messages when using smbldap-populate, smbldap-groupadd, etc. Google produced no useful

I remember in one slide of Prof. Ripley's presentation overhead, he said the most popular data analysis software is excel. So is there any resource or tutorial on this topic? Thank you so much!

There's a new page on the Burns Statistics website http://www.burns-stat.com/pages/Tutor/spreadsheet_addiction.html that looks at spreadsheets from a quality assurance perspective. It presents R as a suitable alternative to spreadsheets. Also there are several specific problems with Excel that are highlighted, including the status of statistical functionality in Excel. Patrick Burns Burns

Hello, I need to perform a mixed-model (with nesting) MANCOVA, using Type III sums of squares. I know how to perform each of these types of tests individually, but I am not sure if performing a mixed-model MANCOVA is possible. Please let me know. Erika <>< <>< <>< <>< <>< <>< <>< Erika Crispo, PhD candidate

R-devotees, I have a question about modeling in the case where the response variable is binary. I have a case where I have a response variable that is the probability of success, and four descriptor variables, The response has a sigmoid response with one of the variables. I would like to test for the effect of the various descriptor variables on the percentage success of the binary trait. I have