Hi John and Peter, Thanks for your reply. I found that fitdistcens, is a good approach. I did that for lognormal, exp ,and other distributions. Values for lnorm from SAS and R were close, but slightly different. At the moment, my main concern is finding the estimated lambda value for poisson for the interval censored data, and it seems there is a problem somewhere and I really appreciate your support.Error:"Error in optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, rcens = rcens, : \n initial value in 'vmmin' is not finite\n" Kind regards,Mohsen Background about my data and code:
I have to say I do not have any idea, > max(z) [1] 39011 > min(z) [1] 1 > I am using library(fitdistrplus). I also passed the start param for optim, but no success as suggested before in some forums earlier. I have provided all scenarios (the first two ones work, the 3rd is my problem, and the 4th also works). And No missing value. I am getting some NAN form gamma also, but I do not know the reason. ------works df= read.csv ("E:/mydata/Motorway-Urban/hour/PathAll_TWOMONTH _BothDirection715_2.csv") z=rep(df$timenum,time=df$count) y<-z ycens <- data.frame(left=y,right=y) max=27219 ct=max for(i in max:28666 ) { ycens$right[ct]=NA ct=ct+1 } ct=1; for(i in 1:28666 ) { if( ycens$left[i]<3) { ycens$left[ct]=NA } if( i>max) { ycens$left[ct]=500 } ct=ct+1 } fitlnc<-fitdistcens(ycens,"pois") > fitlnc Fitting of the distribution ' pois ' on censored data by maximum likelihood Parameters: estimate lambda 93.34093 -----------------Works method 2-------------- z=rep(df$timenum,time=df$count) > y<-z > > ycens <- data.frame(left=y,right=y) > max=27219 > ct=max > for(i in max:28666 ) + { + ycens$right[ct]=NA + + ct=ct+1 + + } > ct=1; > for(i in 1:28666 ) + { + + if( ycens$left[i]<3) + { + ycens$left[ct]=NA + + } + ct=ct+1 + } > fitlnc<-fitdistcens(ycens,"pois") > fitlnc Fitting of the distribution ' pois ' on censored data by maximum likelihood Parameters: estimate lambda 142.0141 ==================PROBLEEEEEEEEEEMMMM====================== z=rep(df$timenum,time=df$count) y<-z ycens <- data.frame(left=y,right=y) max=27219 ct=max for(i in max:28666 ) { ycens$right[ct]=y[ct] ycens$left[ct]=500 ct=ct+1 } ct=1; for(i in 1:28666 ) { if( ycens$left[i]<4) { ycens$left[ct]=1 } ct=ct+1 } > fitlnc<-fitdistcens(ycens,"pois") [1] "Error in optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, rcens = rcens, : \n initial value in 'vmmin' is not finite\n" attr(,"class") [1] "try-error" attr(,"condition") <simpleError in optim(par = vstart, fn = fnobjcens, fix.arg = fix.arg, rcens = rcens, lcens = lcens, icens = icens, ncens = ncens, ddistnam = ddistname, pdistnam = pdistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...): initial value in 'vmmin' is not finite> Error in fitdistcens(ycens, "pois") : the function mle failed to estimate the parameters, with the error code 100 ====================Works========================= z=rep(df$timenum,time=df$count) y<-z ycens <- data.frame(left=y,right=y) max=27219 ct=max for(i in max:28666 ) { ycens$right[ct]=y[ct] ycens$left[ct]=500 ct=ct+1 } ct=1; for(i in 1:28666 ) { if( ycens$left[i]<4) { ycens$left[ct]=1 } ct=ct+1 } fitlnc<-fitdistcens(ycens,"lnorm") fitlnc<-fitdistcens(ycens,"exp") > fitlnc<-fitdistcens(ycens,"gamma") There were 12 warnings (use warnings() to see them) > warnings() Warning messages: 1: In dgamma(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 2: In pgamma(q = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, ... : NaNs produced 3: In pgamma(q = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 4: In dgamma(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 5: In pgamma(q = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, ... : NaNs produced 6: In pgamma(q = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 7: In dgamma(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 8: In pgamma(q = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, ... : NaNs produced 9: In pgamma(q = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 10: In dgamma(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced 11: In pgamma(q = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, ... : NaNs produced 12: In pgamma(q = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... : NaNs produced Remove Ads On Monday, February 15, 2016 3:40 AM, John Kane <jrkrid...@inbox.com> wrote: Thank you, kind sir, you are correct but I was too rushed to write more as the bread needed to be taken out of the oven. John Kane Kingston ON Canada > -----Original Message----- > From: pda...@gmail.com > Sent: Sun, 14 Feb 2016 15:37:22 +0100 > To: jrkrid...@inbox.com > Subject: Re: [R] Estimating Mean of a Poisson Distribution Based on > Interval censoring > > Fortune candidate :-) > > However, the more scientific approach would be to ask for evidence to be > scrutinized, acknowledging that R might be fallible, however unlikely > that may seem. > > Also, there is always the possibility that there are two answers because > the question is not the same. > > -pd > >> On 14 Feb 2016, at 14:35 , John Kane <jrkrid...@inbox.com> wrote: >> >>> By the way, is there anything for lognormal?I think fitdistcens is not >>> good for this purpose as it gives me different result compared to SAS >> >> The general assumption is that if Excel or any other spreadsheet gives a >> result that is different from R then R will be correct. >> >> Generally with SAS it may be that R is correct or just that R and SAS >> use slightly different algorithms. >> >> John Kane >> Kingston ON Canada >> >> >>> -----Original Message----- >>> From: r-help@r-project.org >>> Sent: Sat, 13 Feb 2016 08:45:02 +0000 (UTC) >>> To: r-help@r-project.org >>> Subject: [R] Estimating Mean of a Poisson Distribution Based on >>> Interval >>> censoring >>> >>> Dear all, >>> I appreciate that if you let me know if there is any package >>> implemented >>> in R for Estimating Mean of a Poisson Distribution Based on Interval >>> censoring? And if yes, could you please provide some information about >>> it:) >>> By the way, is there anything for lognormal?I think fitdistcens is not >>> good for this purpose as it gives me different result compared to SAS >>> and >>> only useful for right/left censoring and not interval censoring (or >>> both >>> left and right together). >>> Kind regards,Mohsen >>> [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> >> ____________________________________________________________ >> Can't remember your password? Do you need a strong and secure password? >> Use Password manager! It stores your passwords & protects your account. >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Office: A 4.23 > Email: pd....@cbs.dk Priv: pda...@gmail.com ____________________________________________________________ FREE ONLINE PHOTOSHARING - Share your photos online with your friends and family! [[elided Yahoo spam]] [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.