similar to: RE gap statistic in cluster analysis

Dear List Has anyone used R to distnguish between alternative forecasting models? In particular is the Diebold Mariano test available for use within R. Any assistance would be greatly appreciated. Graham Leask Lecturer in Strategy Economics & Strategy Group Aston University Aston Triangle Birmingham B4 7ET Tel: 0121 204 3150 E Mail: g.leask at aston.ac.uk

Dear List I am looking for a script that will calculate the Box M test to test the homogeneity of the variance/covariance matrix between two matrices. If anyone could send me the script I would appreciate it. I am aware of the scepticism about this test, where due to extreme sensitivity a p value of 0.01 is recommended. Despite this however Box's M test is the established

Is there a function available in R that implements Mojena's Upper Tail Rule or that draws a Mojena plot? I would also like to find a function that implements Duda and Hart's stopping rule. Finally with function cophenet how can I achieve a straightforward Cophenet correlation coefficient (i.e. one number for example 0.876) that gives the agreement between the structure of the

I have a set of data that consists of a number of biological measurements. The columns are Time that runs from 01/01/2005 to 01/5/2007, Group which has 23 levels and postcode which is nested within group. This is a balanced panel but the number of postcodes differs within groups, from 15 to 400. The rest of this data consists of a number of columns of quantitative measures, largely counts.

I have two data frames with a number of common variables that I wish to put into "long format". The first contains the variables es(Csales) [1] "terr" "Dec.02" "Jan.03" "Feb.03" "Mar.03" "Apr.03" "May.03" "Jun.03" [9] "Jul.03" "Aug.03" "Sep.03" "Oct.03"

Does any package available in R contain the V-fold cross-validation method for determining the right number of clusters? Any help greatly appreciated Kind regards Dr Graham Leask Economics and Strategy Group Aston Business School Aston University Aston Triangle Birmingham B4 7ET Tel: Direct line 0121 204 3150 email g.leask@aston.ac.uk [[alternative HTML version deleted]]

Which files are needed to build clang? Is it clang-3.0rc2 and llvm-3.0rc3 or do I need the whole test suite? John Dr John P. Fletcher Tel: (44) 121 204 3389 (direct line), FAX: (44) 121 204 3678 Chemical Engineering and Applied Chemistry (CEAC), Associate Dean - External Relations, School of Engineering and Applied Science (EAS), Aston University, Aston Triangle, BIRMINGHAM B4 7ET 

Removing rows with NAs, using na.omit(), doesn't seem to be working for me. Dataset: > str ( ex10s ) 'data.frame': 2189576 obs. of 5 variables: $ LOPNR : int 58 58 58 58 64 64 64 64 64 64 ... $ DIAGNOS: Factor w/ 173 levels "F20","F200","F2000",..: 128 128 128 128 105 105 105 160 105 105 ... $ X_DATE : int 20060821 20061207 20080102 20090904

Thanks. I was "believing" an Excel import of the file - as you say, a re-import into R still has 333 columns. I shall look elsewhere for the cause of the mysterious truncation. Stuart > ----- Original Message ----- > From: "Thomas Lumley" <tlumley at u.washington.edu> > To: "Stuart Leask" <stuart.leask at nottingham.ac.uk> > Cc:

Hi Stuart, I often use this small function standardize <- function(x) ( x - mean(x, na.rm=T) ) / sqrt(var(x, na.rm=T)) to standardize variables. You should be able to use this to do what you want by splitting the data frame into sections based on the factor level, using standardize() to create a new variable in each section, then paste the data frame back together. Something like: #

Dear List members I have a large dataset organised in choice groups see sample below +-------------------------------------------------------------------------------------------------+ | dn obs choice acid br date cdate situat~n mth year set |

On Nov 7, 2011, at 2:00 PM, Bill Wendling wrote: > Good day, LLVMers! > > We are starting on our third (and hopefully last) round of testing for LLVM 3.0. Please visit: > > http://llvm.org/pre-releases/3.0/rc3/ > > for the sources. There are also binaries for Darwin up there, with more to come during the week. Please build this release candidate, test it out on your

Dear List I am trying to fit a multinomial model using the mlogit package. Attempting to load the data into mlogit presents the following error. MLOG<-mlogit.data(Mult3,shape="long",choice="CHOICE",alt.var="mode.ids",indivs = "set3",chid.var = "obs") Error in `row.names<-.data.frame`(`*tmp*`, value = c("1.1", "1.2",

Dear List How do you change the colour settings for the banner/silhouette plot? I am trying to produce a black and white plot of publication quality. Is there a way to set black and white plots as the default for R graphics? Any help greatly appreciated. Graham Leask Economics & Strategy Group Aston University [[alternative HTML version deleted]]

(Many thanks to David Barron & Jonathan Baron for pointing me to 'recode' in the 'car' package). I think I've been told this before, but how do I search for a function/keyword in libraries I don't yet have installed? (ie. on the CRAN site I tried the search engines with "recode" etc., but didn't pick up the car package this way) Stuart Dr Stuart Leask

I am looking to fit one or more latent categorical variables to data that is a mixture of categorical and continuous variables. Factor analysis would work for continuous data, latent class analysis for categorical data. I understand that in a package such as MPlus I could perform a single analysis of both data types. Are there similar routines available in R? Stuart -----Original Message-----

I have a large dataset (~1 million rows) of three variables: ID (patient's name), DATE (of appointment) and DIAGNOSIS (given on that date). Patients may have been assigned more than one diagnosis at any one appointment - leading to two rows, same ID and DATE but different DIAGNOSIS. The diagnoses may change between appointments. I want to subset the data in two ways: - define groups

Hi list, I tried to load the package SAGx and failed because it complains it's looking for the Biobass which is not there. Then I looked up the package list and Biobass is not found. I'm trying to run the Jonckheere-Terpstra test and from what I see in the R archive, SAGx is the only place it's been implemented. > library(SAGx) Loading required package: multtest Loading required

Hello All, I have a working port of R on my SL5500. I've not tested the X windowing support yet, but was more concerned about the accuracy of the fp emulation. The following is the result of the test which Stuart Leask recommended I should try: Mandrake 8.2 > x<-NA > is.na(x) [1] TRUE > x+1 [1] NA > 2*x [1] NA Zaurus OZ3 > x<-NA > is.na(x) [1] TRUE > x+1 [1] 1

Full_Name: Alexandra R Mendes de Almeida Version: 2.4.1 OS: Linux Submission from: (NULL) (201.51.225.154) R-Masters The packahe SGAx is not on the repository. See the message returned by R when i tried to install it: > install.packages("SAGx") --- Please select a CRAN mirror for use in this session --- Loading Tcl/Tk interface ... done Warning in download.packages(unique(pkgs),