Dear steve: I always run SAS 9.3 on a 64 bit Windows XP machine, which is the same as yours! When I installed this 9.3 version, some lauguage module was ignored, but I don't think this impair the operation process! The code that mentioned previously does't work despite I have submitted it many times. Could you pls copy the right code to this forum or my email ( zhenqiangxu@163.com)? Take example 37.2 as an example again, supposed I can obtain a truncated normal model, the PDF of this truncated normal : where: cunormal = cumulative normal correction factor to allow for truncation, m and s = mean and standard deviation of the interval lengths distribution and x = logint, 7.5 is the point for truncation. What I really concern is that how can I get the point at which the PDF accounted for exactly half of the observed frequency? Maybe the FMM procedure is not the unique and best way to obtain what I need, so Mr. Steve, could you help me to solve this crucial problem using either other basic codes or the FMM code? Thanks a lot and best regards! ... View more

Dear Steve: Thank you for your kind and professional reply！ Example.37.2 “The Usefulness of Custom Starting Values: When Do Cows Eat?” is indeed a good starting place. Taking it as an example, supposing the entered original data are unchanged (including logInt and relevant counts), if I only want to fit the posterior part of the data after the x-axis point 7.9 (clear part of simulative image 2), using only a truncated (truncation=7.9) normal distribution regardless of the distribution pattern for the anterior part (obscure part of simulative image2), what can I do? I use the below SAS code to obtain relative info: proc fmm data=cattle;      model logint = / dist=truncnormal(7.9,.);      freq count; run; But it doesn't work, following by the warning info :"Adequate starting values could not be determined for this model. The model is probably over-parameterized and contains too many components." Does my code wrong? ... View more

Thanks for reminding, my SAS sofeware actually have a little problems when installing, FROOT function is not available in my computer, but the bisection method is OK. Then I change the statement as below: proc iml; start func(x);    f1 = pdf("Normal", x, 12.7, 6.7); /* density of N(12.7,6.7), where 6.7 is std dev in your example*/    f2 = pdf("Normal", x, 37.3, 3);    return( f1 - f2 ); finish; start bisection(a, b); dx = 1e-6; dy = 1e-4; do i = 1 to 100;   c = (a+b)/2;   if abs(func(c)) < dy | (b-a)/2 < dx then   return(c);   if func(a)#func(c) > 0 then a = c;   else b = c; end; return (.); finish; z = bisection(27, 37); print z; Then the SAS procedure determines the solution is "Z=29.03". Is the statement mentioned above right or wrong? By the way, you said that the function f(x) - f1(x)-f2(x) is zero at the crossing point,but why return(f1-f2) in the func(x), is that meaning f1(x)-f2(x)=0??? Looking forward your friendly answer! Many thanks and best regards! ... View more

Dear Rick: Thanks so much for your reply, and it must give me good suggestion to solve my question. Given the accurate data which I want to obtain, the function and method referring to FROOT function is preferred. In strict accordance with your statement in SAS/IML 12.1, I try to fix these statements in your example illustrating the distribution of Scrabble® scores which is characterized by a mixture of two normal distributions upon your score. proc iml; start func(x);    f1 = pdf("Normal", x, 21.7, 6.7); /* density of N(21.7,6.7), where 2 is std dev in your example*/    f2 = pdf("Normal", x, 37.3, 3);    return( f1 - f2 ); finish; x = froot("Func", {27 37}); print x; However, after performing, the error terms occur : "Matrix x has not been set to a value". What does it mean? And any errors in my statements?? If have, could you please tell me?? Thank you for your helpful assistance. ... View more