Displaying 20 results from an estimated 3000 matches similar to: "How to define proper breaks in RFM analysis"
2017 Oct 13
0
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
2017 Oct 13
2
How to define proper breaks in RFM analysis
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
2017 Oct 13
0
How to define proper breaks in RFM analysis
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
2017 Oct 06
3
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
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
2017 Oct 05
0
RFM Analysis Help
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
2017 Oct 13
2
How to define proper breaks in RFM analysis
> 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,
2017 Oct 13
0
How to define proper breaks in RFM analysis
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
2017 Oct 23
1
How to define proper breaks in RFM analysis
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
2017 Aug 16
5
strange behaviour read.table and clipboard
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 ...
2017 Jul 10
4
fit lognorm to cdf data
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
2017 Jul 04
6
R and UBUNTU startup
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
2018 Feb 08
2
plotting the regression coefficients
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
2017 Jun 26
1
Model studies in one analysis using treatment as a five level moderator in a meta-regression
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
2018 Feb 08
2
plotting the regression coefficients
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 <-
2017 Aug 17
2
strange behaviour read.table and clipboard
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".
2004 Aug 21
3
Puzzled at lm() and time-series
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.
2018 Feb 16
2
Putting 733 discrete categories on Y-axis in qqplot2 as they are
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,
2017 Aug 15
2
strange behaviour read.table and clipboard
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
>
2017 Aug 08
2
how to extract individual values from varcomp?
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
2018 Feb 15
2
Putting 733 discrete categories on Y-axis in qqplot2 as they are
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