search for: cscores

Hi Hemant, Here is an example that might answer your questions. Please don't run previous code as it might not work. I define the break values as arguments to the function (rbreaks,fbreaks,mbreaks) If you want the breaks to work, make sure that they cover the range of the input values, otherwise you get NAs. # expects a three (or more) column data frame where # column 1 is customer ID,

In their paper, "Lexical Scope and Statistical Computing", the authors ( Gentleman and Ihaka ) go to great length explaining why R's use of lexical scoping creates advantages when doing statistical computations. If anyone has or is familiar with this paper, could they provide the main program code for how the "newton" function would be called in their example on page 500

I'm getting all the rows as NA in Cscore and almost most of the observation in R and F and M are also NA. what can be the reason for this. also suggest me the appropriate solution. On 9 October 2017 at 15:51, Jim Lemon <drjimlemon at gmail.com> wrote: > Hi Hemant, > Here is an example that might answer your questions. Please don't run > previous code as it might not work.

I seriously doubt that you are running the code I sent. What you have probably done is to run your data, which has a different date format, without changing the breaks or the date format arguments. As you haven't provided any example that shows what you are doing, I can't guess what the problem is. Jim On Mon, Oct 9, 2017 at 9:40 PM, Hemant Sain <hemantsain55 at gmail.com> wrote:

Full_Name: Heather Turner Version: 2.2.0 OS: Windows XP Submission from: (NULL) (137.205.240.44) Standardized residuals as calculated by rstandard.lm, rstandard.glm and plot.lm are Inf/NaN rather than zero when the un-standardized residuals are zero. This causes plot.lm to break when calculating 'ylim' for any of the plots of standardized residuals. Example:

Hello Jim, i have converted all my variable data type according to your attached example including date, and my dataset looks like this. ID purchase date 1234 10.2 2017-02-18 3453 18.9 2017-03-22 7689 8 2017-03-24 but when I'm passing the data

Dear collegues, Using maxstat I am getting the following: > blood <- maxstat.test(Surv(SUPER, FV)~ZAP,data=zap70, smethod="LogRank") Error in maxstat(y = structure(c(24.4301369863014, 26.4164383561644, 18.7835616438356, : couldn't find function "cscores" I do not know the meaning of this problem. Could you please help me on dat? Thank you in advance for your time. Sincerely, Francesc Bosch, M.D. Senior specialist Department of Hematology, Hospital Clinic C/ Villarroel, 170 08036 - Barcelona Phone & Fax: +34-93-227 5428 e-mail: fbosch...

I'm trying to perform an RFM analysis on the attached dataset, I'm able to get the results using the auto_rfm function but i want to define my own breaks for RFM. as follow r <-c(30,60,90) f <-c(2,5,8) m <-c(10,20,30) but when i tried to define my own breaks i got the identical result for RFM i.e 111 for every ID. please help me with this with working R script so that i can get

Dear all, can somebody give me some pointer how I can fit a "linear-by-linear association model" (i.e. loglinear model for the ordinal variables) in R? A brief description can be found here 'https://onlinecourses.science.psu.edu/stat504/node/141'. Thanks for your help

Hi Hemant, Let's take it one step at a time. Save this code as "qdrfm.R" in your R working directory: It includes the comments I added last time and fixes a bug in the recency scoring. qdrfm<-function(x,rbreaks=3,fbreaks=3,mbreaks=3, date.format="%Y-%m-%d",weights=c(1,1,1),finish=NA) { # if no finish date is specified, use current date if(is.na(finish))

Dear R users, I m quite a novice in using R for factor analysis and I would need some help to choose the right function. I have a contingency table and I would like to perform a Correspondence analysis on this table, followed by a hirarchical clustering of my variables projected in on the first principal components. Here are my question : - what is the more appropriate function to do so ...

This bug is not quite fixed - the example from my original report now = works using R-2.2.1, but plot(Uniform, 6) does not. The bug is due to if (show[6]) { ymx <- max(cook, na.rm =3D TRUE) * 1.025 g <- hatval/(1 - hatval) # Potential division by zero here # plot(g, cook, xlim =3D c(0, max(g)), ylim =3D c(0, ymx),=20 main =3D main, xlab =3D

Hello, I need help in performing a Van_der_Waerden normal scores test in R. I have two arrays of scores(final on therapy scores from drug and placebo) and want to use the normal scores procdeure to test for significance. (observations are unequal in number - due to dropouts). Could you please help me out with the coding or let me know if there is a package that can be used (for example,