Hi all,
I am trying to learn how to use streg for generalized gamma
estimation. So far i have been unsuccessful in doing so because i am
unable to get convergent solution. My question to you all is whether
i am missing smt out while invoking streg or using it improperly.
Below i have attached the small piece of code i have been working
with. It tries to generate log normal data and then tries to fit
generalized gamma model to it. (lognormal is a special case of
generalized gamma)
Please have a look at it. Thanks in advance.
set obs 10000
obs was 0, now 10000
. set seed 753
. gen x = 2*uniform()
. quietly summ x
. local meanx r(mean)
. gen e1 = invnormal(uniform())
. gen e2 = 2*invnormal(uniform())
. local b01 = ln(1)- `meanx' - 0.5*1
. local b02 = ln(1)- `meanx' - 0.5*2
. forvalues i = 1/2 {
2. gen y`i' = exp(`b0`i'' + x + e`i')
3. }
. forvalues j = 1/2 {
2. stset y`j'
3. streg y`j' x, d(gamma) robust skip difficult nonrtolerance
4. matrix beta`j' = e(b)
5. matrix stdev`j' = vecdiag(e(V))
6. }
failure event: (assumed to fail at time=y1)
obs. time interval: (0, y1]
exit on or before: failure
------------------------------------------------------------------------------
10000 total obs.
0 exclusions
------------------------------------------------------------------------------
10000 obs. remaining, representing
10000 failures in single record/single failure data
11958.73 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 56.57502
failure _d: 1 (meaning all fail)
analysis time _t: y1
Iteration 0: log pseudolikelihood = -21029.662 (not concave)
Iteration 1: log pseudolikelihood = -17755.326 (not concave)
Iteration 2: log pseudolikelihood = -11915.691 (not concave)
Iteration 3: log pseudolikelihood = -9081.0115
Iteration 4: log pseudolikelihood = -7834.9916
discontinuous region encountered
cannot compute an improvement
r(430);
end of do-file
r(430);
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