similar to: Number of cluster

Hi, I have a 1.000 observations with 10 attributes (of different types: numeric, dicotomic, categorical ecc..) and a measure M. I need to cluster these observations in order to assign a new observation (with the same 10 attributes but not the measure) to a cluster. I want to calculate for the new observation a measure as the average of the meausures M of the observations in the cluster

All, How can we find a distance matrix for categorical data ie. given a csv below var1 var2 var3 var4 element1-1 yes x a k element1-2 no y b l element1-3 maybe y c m how can i compute the distance matrix between all the elements Actually i need it to create clusters on top

On 31/01/2018 6:33 AM, Joris Meys wrote: > 3. given your criticism, I'd like your opinion on where I can improve > the documentation of https://github.com/CenterForStatistics-UGent/pim. > I'm currently busy updating the help files for a next release on CRAN, > so your input is more than welcome. After this invitation I sent some private comments to Joris. I would say his

I think you are confusing package and function here. Plus some of the R Core packages, that you mention, contain functions that should probably be replaced by functions with better implementation from packages on CRAN. Best regards Morgan On Fri, 11 Oct 2019 15:22 Joris Meys, <jorismeys at gmail.com> wrote: > > > On Fri, Oct 11, 2019 at 3:55 PM Morgan Morgan <morgan.emailbox

Hi, I want to give a summary or anova for "arima" model in R, as "summary", and "anova" for "lm". As including various intervention factors in arima(xreg = ) part, I want to assess the significancy of thse factors. I can do it using interrupted analysis of time series by linear regression, but want to see whether arima model works for the data first.

can anyone know where i can find information on compile hmisc on windows, especially 64 windows? thanks, _________________________________________________________________ The New Busy is not the too busy. Combine all your e-mail accounts with Hotmail. ID28326::T:WLMTAGL:ON:WL:en-US:WM_HMP:042010_4 [[alternative HTML version deleted]]

Dear all, I tried to read in a 3.8Gb RDS file on a computer with 16Gb available memory. To my astonishment, the memory footprint of R rises quickly to over 13Gb and the attempt ends with an error that says "cannot allocate vector of size 5.8Gb". I would expect that 3 times the memory would be enough to read in that file, but apparently I was wrong. I checked the memory.limit() and that

Dear All: stepping in late, but @Joris, if you would like to take 'from a single file' literally, have a look at: https://github.com/bpfaff/lp4rp (lp4rp: literate programming for R packages); Cheers, Bernhard ps: incidentally, within the noweb-file roxygen is employed. -----Urspr?ngliche Nachricht----- Von: R-devel [mailto:r-devel-bounces at r-project.org] Im Auftrag von Joris

And now I've seen I copied the wrong part of ?is.na > The default method for is.na applied to an atomic vector returns a logical vector of the same length as its argument x, containing TRUE for those elements marked NA or, for numeric or complex vectors, NaN, and FALSE otherwise. Key point being "atomic vector" here. On Sat, Jun 9, 2018 at 1:41 PM, Joris Meys <jorismeys at

Dear all, I want to apply a weighted median on a huge dataset, and I remember a function from the package R.basic that could do this using an internal sorting algorithm qsort. This speeded things up quite a bit. Alas, I can't find that package anywhere anymore. There is a weighted.median function in the package limma too, but I didn't use that before. Anybody who knows what happened to

Dear all, to my astonishment data.table cannot be installed on R 3.5 Windows. When checking the package page, the Windows binary is available for download. When checking the server however, I can't seem to find data.table. Also install.packages() says the package is only available in source form and may need compilation. Compiling using Rtools 35 is no problem. Is this merely an issue of

Hi all, I understand that gls() uses generalized least squares, but I thought that maybe optimum weights from gls might be used as weights in lm (as shown below), but apparently this is not the case. See: library(nlme) f1 <- gls(Petal.Width ~ Species / Petal.Length, data = iris, weights = varIdent(form = ~ 1 | Species)) aa <- attributes(summary(f1)$modelStruct$varStruct)$weights f2 <-

Dear all, I've noticed by trying to download gz files from here : https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM907811 At the bottom one can download GSM907811.CEL.gz . If I download this manually and try oligo::read.celfiles("GSM907811.CEL.gz") everything works fine. (oligo is a bioConductor package) However, if I download using download.file("

Thank you. I was just replying my own message with the same information. Sorry for not doing the research properly before filing. Cheers Joris On Sat, Mar 24, 2018 at 11:36 AM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 24/03/2018 6:16 AM, Joris Meys wrote: > >> Dear all, >> >> while preparing some exercises I came across some highly surprising

Joris, the point is that 'z' is NOT used as a predictor in the model. Therefore it should not affect predictions. Also, I find it suspicious that the error only occurs when the response variable conitains missings and 'z' is unique (I have tested several other cases to confirm this). -Mark Op vr 16 mrt. 2018 om 13:03 schreef Joris Meys <jorismeys at gmail.com>: >

Dear all, as a follow-up to the question asked on R-package-devel (see link below): Someone sent a package to CRAN with a few problems. There's more things wrong with the submission, but one thing that really caught my eye was the following error: Warning message: running command '"C:/PROGRA~1/R/R-33~1.2/bin/x64/R" CMD BATCH --vanilla "testthat.R"

Dear colleagues, I teach statistics using SPSS. I want to use R instead. I hit on one problem and I need some quick advice. When I want to work with ordinal variables, in SPSS I can compute the median or create a barchart or compute a spearman correlation with no problems. In R, if I "read" the ordinal variable as numeric, then I cannot do a barplot because I miss the category names. If

Indeed. as_date is from lubridate, but the same holds for as.Date. The output and it's interpretation should be consistent, otherwise it leads to confusion when programming. I understand that the difference exists after asking a question on Stack Overflow: https://stackoverflow.com/q/50766089/914686 This understanding is never mentioned in the documentation - that an Inf date is actually

On 08/30/2018 01:56 PM, Joris Meys wrote: > I have to agree with Emil here. && and || are short circuited like in C and > C++. That means that > > TRUE || c(TRUE, FALSE) > FALSE && c(TRUE, FALSE) > > cannot give an error because the second part is never evaluated. Throwing a > warning or error for > > c(TRUE, FALSE) || TRUE > > would mean

Dear list, I'm looking for an inverse function of melt(which is in package reshape).Namely, I had a data frame like this (Table1) YEAR VAR1 VAR2 VAR3 1995 7 3 45 1996 5 6 32 1997 6 10 15 I transformed my data by using the melt function and my data was reshaped in the following format: (Table2) YEAR variable