similar to: How to define proper breaks in RFM analysis

Hi Your statement about attaching data is problematic. We cannot do much with it. Instead use output from dput(yourdata) to show us what exactly your data look like. We also do not know how do you want to split your data. It would be nice if you can show also what should be the bins with respective data. Unless you provide this information you probably would not get any sensible answer. Cheers

Hey, i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to

Hi You expect us to solve your problem but you ignore advice already recieved. Your data are unreadable, use dput(yourdata) instead. see ?dput > test<-read.table("clipboard", heade=T) Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 115 did not have 6 elements What is ?ideal interval? can you define it? Should it be such to provide eqal

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

Hi Hemant, As I suspected, the code broke when I got to the line: result <- rfm_auto(df, id="user_id", payment ="subtotal_amount", date="created_at") Error in rfm_auto(df, id = "user_id", payment = "subtotal_amount", date = "cr eated_at") : could not find function "rfm_auto" It looks like you are using the hoxo-m/easyRFM

> On Oct 13, 2017, at 2:51 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > You expect us to solve your problem but you ignore advice already recieved. > > Your data are unreadable, use dput(yourdata) instead. see ?dput > >> test<-read.table("clipboard", heade=T) > Error in scan(file = file, what = what, sep = sep, quote = quote,

Hemant's problem is that the indicators are not distributed uniformly. With a uniform distribution, categorization gives a reasonably optimal separation of cases. One approach would be to drop categorization and calculate the overall score as the mean of the standardized indicator scores. Whether this is an option I do not know. I did offer an "eyeball" set of breaks in a previous

hello, I'm confused what you guys are talking about. i just want to set ideal threshold values for my RFM scores which can be done using Quantiles but i don't want to use quantiles because my data is not normally distributed so it will lead to wrong ranges of breaks. to fix this problem I'm looking for an approach which can define the ideal range to breaks to categorize RFM scores into

Hi Duncan The simples spreadsheet is: Put a name in the cell, let say "a1" Put number e.g. 1 below "a1" Copy the number to enough rows Select this column and press ctrl-c result is > temp<- read.delim("clipboard") > str(temp) 'data.frame': 1513 obs. of 1 variable: $ a1: Factor w/ 2 levels "1","a1": 1 1 1 1 1 1 1 1 1 1 ...

Dear all I am struggling to fit data which form something like CDF by lognorm. Here are my data: proc <- c(0.9, 0.84, 0.5, 0.16, 0.1) size <- c(0.144, 0.172, 0.272, 0.481, 0.583) plot(size, proc, xlim=c(0,1), ylim=c(0,1)) fit<-nls(proc~SSfpl(size, 1, 0, xmid, scal), start=list(xmid=0.2, scal=.1)) lines(seq(0,1,.01), predict(fit, newdata=data.frame(sito=seq(0,1,.01))), col=2) I tried

Dear all I have 3 questions. Due to some reason I switched from Vista to Ubuntu on home PC. I was used to start with Rgui.exe. However I am not able to find it under Ubuntu and R starts as terminal (probably Rterm). Question 1. Is Rgui.exe available on linux? In Windows doc folder I can find manuals, however I did not find doc folder in Ubuntu. I found somewhere that manuals need to be

Hi Petr; Thanks for your reply. It is much appreciated. A small example is given below for 4 independent and 4 dependent variables only. The values given are regression coefficients.I have looked ggplot documents before writing to you. Unfortunately, I could not figure out as my experience in ggplot is ignorable Regards. Greg y1 y2 y3 y4 x1 -0.19 0.40 -0.06 0.13 x2 0.45 -0.75 -8.67 -0.46 x3

Dear Vito, Thank you for your reply. I tried to contact the statistics departement numerous times, but did not receive any reply. That is why I started to look on the internet for help. Yours sincerely, Jay Verstuurd vanaf mijn iPhone > Op 26 jun. 2017 om 22:05 heeft Vito Michele Rosario Muggeo <vito.muggeo at unipa.it> het volgende geschreven: > > hi Jay, > Consult a local

Hi Petr; Thanks so much. Exactly this is what I need. I will play to change color and so on but this backbound is perfect to me. I do appreciate your help and support. Regards, Greg On Thu, Feb 8, 2018 at 1:29 PM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > Hi > > I copied your values to R, here it is > > > > > dput(temp) > > > > temp <-

Hi > -----Original Message----- > From: Robert Baer [mailto:rbaer at atsu.edu] > Sent: Wednesday, August 16, 2017 3:04 PM > To: PIKAL Petr <petr.pikal at precheza.cz>; Duncan Murdoch > <murdoch.duncan at gmail.com> > Cc: r-devel at r-project.org > Subject: Re: [Rd] strange behaviour read.table and clipboard > > You said, "put a name in the cell".

Hi Petr; I would like to get a plot with names as they are in the original file. They are chemical names and I have 733 in the my file. For example, let me give to chemical names "*2-hydroxybutyrate/2-hydroxyisobutyrate*" and "*palmitoyl-arachidonoyl-glycerol (16:0/20:4) [1]**" .So, what should I put [c(2,3,1)] part in the command: iris$MySpecies<-factor(iris$Species,

I tried toy problems and there doesn't seem to be a basic problem between lm() and ts objects: X = data.frame(x=c(1,2,7,9), y=c(7,2,3,1)) lm(y ~ x, X) X <- lapply(X, function(x) ts(x, frequency=12, start=c(1994,7))) lm(y ~ x, X) and this works fine - whether you do an lm() before or after making ts objects, it's okay. But I have a situation where things aren't okay.

Dear all I used to transfer data from excel to R by simple ctrl-c and read.delim("clipboard") construction. I know it is a bad practice but it is easy and for quick exploratory work it is OK. However after changing to new R devel few days ago I encountered weird behaviour. I tried one or two columns. In case of 2 columns, header is repeated after 526 items >

Hello, I am trying to use varcomp to decompose the variance across multiple nested levels on a lme object. I am able to successfully do this and when I view the varcomp object I can see the individual values / estimates for the variance at different levels. However, I want to be able to extract each of them separately, as I need to build a confidence interval using bootstrapping on the sample

Hi all; I have 733 discrete categories that will go on y-axis in ggplot2. I used the following command to put the name of x-axis. scale_x_discrete (limits = c("SI", "HOMAIR", "AIR","HOMAB","SG","DI","FI","FG")) Since there are only 8 categories on x it was easy to do. Is there any way to do the same for 733 discrete