Displaying 9 results from an estimated 9 matches for "fscore".
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2017 Oct 09
1
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)
...sh<-as.Date(date(), "%a %b %d %H:%M:%S %Y")
x$rscore<-as.numeric(finish-as.Date(x[,3],date.format))
x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE))
custIDs<-unique(x[,1])
ncust<-length(custIDs)
rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust),
fscore=rep(0,ncust),mscore=rep(0,ncust))
rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE)
rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE)
rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE)
rfmout$cscore<-(weights[1]*rfmout$rscore+
weigh...
2017 Oct 09
2
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
...;)
>> x$rscore<-as.numeric(finish-as.Date(x[,3],date.format))
>> x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE))
>> custIDs<-unique(x[,1])
>> ncust<-length(custIDs)
>> rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust),
>> fscore=rep(0,ncust),mscore=rep(0,ncust))
>> rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE)
>> rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE)
>> rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE)
>> rfmout$cscore<...
2017 Oct 09
0
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
...a %b %d %H:%M:%S %Y")
> x$rscore<-as.numeric(finish-as.Date(x[,3],date.format))
> x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE))
> custIDs<-unique(x[,1])
> ncust<-length(custIDs)
> rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust),
> fscore=rep(0,ncust),mscore=rep(0,ncust))
> rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE)
> rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE)
> rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE)
> rfmout$cscore<-(weights[1]*rf...
2017 Oct 10
0
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
...-as.numeric(finish-as.Date(x[,3],date.format))
> >> x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE))
> >> custIDs<-unique(x[,1])
> >> ncust<-length(custIDs)
> >> rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust),
> >> fscore=rep(0,ncust),mscore=rep(0,ncust))
> >> rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE)
> >> rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE)
> >> rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE)
> >&g...
2013 Mar 18
1
"save scores" from sem
I'm not aware of any routine that those the job, although I think that
it could be relatively easily done by multiplication the manifest
variable vector with the estimates for the specific effect.
To make an example:
v1; v2; v3; v4 are manifest variables that loads on one y latent
variablein a data frame called "A"
the code for the model should be like:
model <-specifymodel(
y
2017 Oct 06
3
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
I'm trying to perform an RFM analysis on the attached dataset,
I'm able to get the results using the auto_rfm function but i want to
define my own breaks for RFM.
as follow
r <-c(30,60,90)
f <-c(2,5,8)
m <-c(10,20,30)
but when i tried to define my own breaks i got the identical result for RFM
i.e 111 for every ID.
please help me with this with working R script so that i can get
2003 May 01
0
factanal
...-0.417 -0.620 -0.519 0.694 0.648
# 1.460 1.038 0.532 1.261 -0.364 0.848
# -0.639 0.888 0.306 -0.372 -0.305 1.101
# 0.779 1.595 0.775 0.499 1.215 -1.055
# 1.304 0.702 0.844 0.688 0.992 0.488
# ;
#
# proc factor data=x corr method=ml nfactors=2 prerotate=varimax rotate=promax out=fscores score;
# run;
#
# proc print data=fscores;
# var factor1 factor2;
# run;
#
# The factor scores one obtains:
# Obs Factor1 Factor2
# 1 -1.00830 -2.12208
# 2 -1.76352 0.09283
# 3 -0.23031 0.96792
# 4 0.06982 -0.01378
# 5 -0.24...
2017 Oct 11
0
RFM analysis
...se freqency",range(table(x[,1])),"\n")
cat("Range of purchase amount",range(by(x[,2],x[,1],sum)),"\n")
custIDs<-unique(x[,1])
ncust<-length(custIDs)
# initialize a data frame to hold the output
rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust),
fscore=rep(0,ncust),mscore=rep(0,ncust))
# categorize the minimum number of days
# since last purchase for each customer
rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE)
# categorize the number of purchases
# recorded for each customer
rfmout$fscore<-cut(table(x[,1]),brea...
2000 Mar 07
1
update fails after specific sequence of steps (PR#474)
...fcategory)
Coefficients:
(Intercept) statuslow fcategorylow fcategorymedium
14.72356 -4.60667 0.08089 -1.09511
------------------------ listing of dataset ----------------------------------------
> Moore
subject status conform fcategory fscore
1 1 low 8 low 37
2 2 low 4 high 57
3 3 low 8 high 65
4 4 low 7 low 20
5 5 low 10 low 36
6 6 low 6 low 18
7 7 low 12 medium 5...