[讨论]Why Does Proc NLP cannot Find the MLE Estimate?

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I use proc nlp command to run regression with truncated sample. My regression is to regress return on deps, a bivariate regression. Return is right-skewed with a fat tail and deps is left-skewed also with a fat tail.

Model: Return = a+ b*deps + error ; (return and deps are continuous normally distributed variables. Truncation point: return = 0

My SAS programme is:

proc nlp data = goodnews tech=congra;* goodnews group means all positive return observations, left-truncated sample; parms a b v =0.5; bounds v>0; max l; d = (0-a - b*deps)/v; t = (return - a - b*deps)/v; m = cdf ('Normal',d, 0,1); n = (2*constant ('pi'))**0.5; denom2 =1/(v*(1-m)*n); ex = exp(-0.5*t**2); prob = denom2 * ex; l = log (prob); run; For the right-truncated sample, it works well and produce the same results as I could get from Stata. But for the left-truncated sample, Sas program just cannot find MLE estimate or produce unstable estimate. For my research design, it would be very difficult to interpret the coefficient if I transform both variables into variables more close to normal distribution.How could I solve this problem?

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关键词：estimate cannot canno find Does MLE Why Does cannot NLP

I think that my first question would be: why are you using PROC NLP to do statistical modeling at all? PROC NLP is designed for operations research problems. Try using PROC NLMIXED instead. I also think you have made the problem a lot more complex than you would need if it were written in NLMIXED instead. HTH, David -- David L. Cassell mathematical statistician Design Pathways 3115 NW Norwood Pl. Corvallis OR 97330

[此贴子已经被作者于2005-9-19 7:46:43编辑过]