I have already posted that in attachement - pdf file. I am posting plain text here:
> library(tmvtnorm) > meann = c(55, 40, 50, 35, 45, 30) > covv = matrix(c( 1, 1, 0, 2, -1, -1, + 1, 16, -6, -6, -2, 12, + 0, -6, 4, 2, -2, -5, + 2, -6, 2, 25, 0, -17, + -1, -2, -2, 0, 9, -5, + -1, 12, -5, -17, -5, 36), 6, 6) > df = 4 > lower = c(20, 20, 20, 20, 20, 20) > upper = c(60, 60, 60, 60, 60, 60) > X1 <- rtmvt(n=100000, meann, covv, df, lower, upper) > sum(X1[,1]) / 100000 [1] 54.98258 > sum(X1[,2]) / 100000 [1] 40.36153 > sum(X1[,3]) / 100000 [1] 49.83571 > sum(X1[,4]) / 100000 [1] 34.69571 # "4th element of mean vector" > sum(X1[,5]) / 100000 [1] 44.81081 > sum(X1[,6]) / 100000 [1] 31.10834 And corresponding results received using equation (3) from pdf file: [54.97, 40, 49.95, 35.31, # "4th element of mean vector" 44.94, 31.32] On 9 May 2017 at 22:17, David Winsemius <dwinsem...@comcast.net> wrote: > >> On May 9, 2017, at 1:11 PM, Czarek Kowalski <czarek230...@gmail.com> wrote: >> >> Of course I have expected the difference between theory and a sample >> of realizations of RV's and result mean should still be a random >> variable. But, for example for 4th element of mean vector: 35.31 - >> 34.69571 = 0.61429. It is quite big difference, nieprawdaż? I have >> expected that the difference would be smaller because of law of large >> numbers (for 10mln samples the difference is quite similar). > > I for one have no idea what is meant by a "4th element of mean vector". So I > have now idea what to consider "big". I have found that my intuitions about > multivariate distributions, especially those where the covariate structure is > as complex as you have assumed, are often far from simulated results. > > I suggest you post some code and results. > > -- > David. > > >> >> On 9 May 2017 at 21:40, David Winsemius <dwinsem...@comcast.net> wrote: >>> >>>> On May 9, 2017, at 10:09 AM, Czarek Kowalski <czarek230...@gmail.com> >>>> wrote: >>>> >>>> Dear Members, >>>> I am working with 6-dimensional Student-t distribution with 4 degrees >>>> of freedom truncated to [20; 60]. I have generated 100 000 samples >>>> from truncated multivariate Student-t distribution using rtmvt >>>> function from package ‘tmvtnorm’. I have also calculated mean vector >>>> using equation (3) from attached pdf. The problem is, that after >>>> summing all elements in one column of rtmvt result (and dividing by >>>> 100 000) I do not receive the same result as using (3) equation. Could >>>> You tell me, what is incorrect, why there is a difference? >>> >>> I guess the question is why you would NOT expect a difference between >>> theory and a sample of realizations of RV's? The result mean should still >>> be a random variable, night wahr? >>> >>> >>>> Yours faithfully >>>> Czarek Kowalski >>>> <truncatedT.pdf>______________________________________________ >>>> 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. >>> >>> David Winsemius >>> Alameda, CA, USA >>> > > David Winsemius > Alameda, CA, USA > ______________________________________________ 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.
