[Limdep Nlogit List] Please help
Harold Mayaba
mayabach2009 at yahoo.com
Thu Oct 27 21:23:48 AEDT 2022
Dear Professor Greene and Nlogit users,I sent a text seeking for some help two weeks ago but i did not receive any response. While waiting for someone to respond, i have been teaching myself on how to use Nlogit. Below are the results i got from Nlogit. Please i need some help to check if i'm in the right track. I'm getting errors which are highlighted in yellow. What do i have to do from this point?
Regards
HaroldI
Error 1084: Expectedequation specs. of form U(...) after MODEL:
|-> Removing data with errors
reject;alti=-999$
Error 1:Unrecognized command. (Missing ; ?)
|-> CALC
; ran(12345) $
|-> RPLOGIT
; Lhs=CHOICE
; CHOICES = alti1
, alti2
, alti3
; Model:
U(alti1)
=aalti1 +CAGED*CAGED + ACDOORS*ACDOORS + NPRS*NPRS + CERT1*CERT1 + CERT2*CERT2 +MMORT*MMORT + HMORT*HMORT + PRICE*PRICE/
U (alti2)
=aalti2 +CAGED*CAGED + ACDOORS*ACDOORS + NPRS*NPRS + CERT1*CERT1 + CERT2*CERT2 +MMORT*MMORT + HMORT*HMORT + PRICE*PRICE/
U (alti3)
= None
; Fcn = CAGED(n ),ACDOORS(n ),NPRS(n),CERT1(n),CERT2(n)
,MMORT(n),HMORT(n)
; Correlated
; Halton
; Pds=10
; Pts =100
; maxit = 200
; WTP=caged/price,acdoors/price
,nprs/price
,cert1/price,cert2/price,mmort/price,hmort/price
; Par $
+------------------------------------------------------+
|WARNING: Badobservations were found in the sample. |
|Found 19 badobservations among 9550 individuals. |
|You can use ;CheckData to get a list of these points. |
+------------------------------------------------------+
Hessian is not positive definite at start values.
Error 803: Hessianis not positive definite at start values.
B0 is too far from solution for Newton method.
Switching to BFGS as a better solution method.
Line search at iteration 17 does not improve the function
Exiting optimization
-----------------------------------------------------------------------------
Start values obtained using MNL model
Dependent variable Choice
Log likelihood function -8498.75280
Estimation based on N = 9531, K = 11
Inf.Cr.AIC = 17019.5 AIC/N = 1.786
---------------------------------------
Loglikelihood R-sqrd R2Adj
Constants only ********** .1756 .1739
Note: R-sqrd = 1 - logL/Logl(constants)
Warning: Model doesnot contain a full
set of ASCs. R-sqrd is problematic. Use
model setup with ;RHS=one to get LogL0.
---------------------------------------
Response data are given as ind. choices
Number of obs.= 9550,skipped 19 obs
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
CHOICE| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
CAGED| -.88357*** .06461 -13.68 .0000 -1.01020 -.75694
ACDOORS| 1.41491 .....(Fixed Parameter).....
NPRS| .09041*** .01401 6.46 .0000 .06296 .11786
CERT1| .08503*** .00895 9.50 .0000 .06749 .10257
CERT2| .13907 .....(Fixed Parameter).....
MMORT| -.27848*** .01713 -16.26 .0000 -.31205 -.24491
HMORT| -.71218 .....(Fixed Parameter).....
AALTI1| .10722 .....(Fixed Parameter).....
PRICE| -.11620 .....(Fixed Parameter).....
AALTI2| .26486 .....(Fixed Parameter).....
NONE| -.37207 .....(Fixed Parameter).....
--------+--------------------------------------------------------------------
***, **, * ==> Significance at 1%, 5%, 10% level.
Fixed parameter ... is constrained to equal the value or
had a nonpositive st.error because of an earlier problem.
Model was estimated on Oct 27, 2022 at 09:18:18 PM
-----------------------------------------------------------------------------
Iterative procedure has converged
Normal exit: 58iterations. Status=0, F= .6426683D+04
-----------------------------------------------------------------------------
Random Parameters Multinom. Logit Model
Dependent variable CHOICE
Log likelihood function -6426.68312
Restricted log likelihood -10470.87372
Chi squared [ 39](P= .000) 8088.38121
Significance level .00000
McFadden Pseudo R-squared .3862324
Estimation based on N = 9531, K = 39
Inf.Cr.AIC = 12931.4 AIC/N = 1.357
---------------------------------------
Loglikelihood R-sqrd R2Adj
No coefficients ********** .3862 .3850
Constants only ********** .3766 .3753
At start values -8498.7528 .2438 .2423
Note: R-sqrd = 1 - logL/Logl(constants)
Warning: Model doesnot contain a full
set of ASCs. R-sqrd is problematic. Use
model setup with ;RHS=one to get LogL0.
---------------------------------------
Response data are given as ind. choices
Replications for simulated probs. = 100
Used Halton sequences in simulations.
RPL model with panel has 955 groups
Fixed number of obsrvs./group= 10
Number of obs.= 9550,skipped 19 obs
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
CHOICE| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
|Randomparameters in utility functions..............................
CAGED| -3.89672*** .21748 -17.92 .0000 -4.32296 -3.47047
ACDOORS| 2.50498*** .10415 24.05 .0000 2.30084 2.70912
NPRS| -1.32085*** .18871 -7.00 .0000 -1.69071 -.95098
CERT1| .45899*** .14691 3.12 .0018 .17106 .74693
CERT2| .52836*** .14091 3.75 .0002 .25218 .80454
MMORT| -.71662*** .07380 -9.71 .0000 -.86126 -.57197
HMORT| -1.64829*** .07890 -20.89 .0000 -1.80293 -1.49365
|Nonrandomparameters in utility functions...........................
AALTI1| .73535 .4843D+07 .00 1.0000*********** ***********
PRICE| -.22131*** .00963 -22.97 .0000 -.24019 -.20243
AALTI2| .98003 .4843D+07 .00 1.0000*********** ***********
NONE| -1.71538 .4843D+07 .00 1.0000 *********** ***********
|Diagonalvalues in Cholesky matrix, L...............................
NsCAGED| 3.37667*** .20165 16.75 .0000 2.98145 3.77190
NsACDOOR| .79580*** .11635 6.84 .0000 .56776 1.02383
NsNPRS| .90651*** .10404 8.71 .0000 .70259 1.11043
NsCERT1| .03803 .15239 .25 .8029 -.26065 .33672
NsCERT2| .24861** .12323 2.02 .0436 .00709 .49013
NsMMORT| .15100 .12500 1.21 .2271 -.09401 .39600
NsHMORT| .13264 .14131 .94 .3479 -.14433 .40960
|Belowdiagonal values in L matrix. V = L*Lt.........................
ACDO:CAG| 2.16585*** .11052 19.60 .0000 1.94924 2.38247
NPRS:CAG| -1.75565*** .16547 -10.61 .0000 -2.07996 -1.43133
NPRS:ACD| -.29059** .12683 -2.29 .0219 -.53916 -.04202
CERT:CAG| .39222*** .14720 2.66 .0077 .10371 .68073
CERT:ACD| .25427* .15154 1.68 .0934 -.04274 .55129
CERT:NPR| .74246*** .11386 6.52 .0000 .51929 .96562
CER0:CAG| .38415*** .13671 2.81 .0050 .11621 .65210
CER0:ACD| .02701 .13599 .20 .8426 -.23952 .29353
CER0:NPR| .83787*** .10014 8.37 .0000 .64159 1.03414
CERT:CER| -.22277 .21091 -1.06 .2909 -.63614 .19061
MMOR:CAG| -.50671*** .08597 -5.89 .0000 -.67521 -.33820
MMOR:ACD| -.43917*** .10308 -4.26 .0000 -.64120 -.23714
MMOR:NPR| .09697 .08708 1.11 .2655 -.07370 .26764
MMOR:CER| -.16355 .12911 -1.27 .2052 -.41660 .08950
MMO0:CER| .45088*** .13869 3.25 .0011 .17906 .72271
HMOR:CAG| -1.04303*** .08460 -12.33 .0000 -1.20885 -.87721
HMOR:ACD| -.32097** .16270 -1.97 .0485 -.63985 -.00209
HMOR:NPR| .10747 .10105 1.06 .2875 -.09057 .30552
HMOR:CER| -.16938 .28375 -.60 .5506 -.72552 .38676
HMO0:CER| .64380*** .17109 3.76 .0002 .30846 .97913
HMOR:MMO| -.15210 .16218 -.94 .3483 -.46997 .16577
|Standarddeviations of parameter distributions......................
sdCAGED| 3.37667*** .20165 16.75 .0000 2.98145 3.77190
sdACDOOR| 2.30743*** .11427 20.19 .0000 2.08346 2.53139
sdNPRS| 1.99712*** .15613 12.79 .0000 1.69111 2.30314
sdCERT1| .87817*** .13411 6.55 .0000 .61531 1.14102
sdCERT2| .98069*** .12101 8.10 .0000 .74351 1.21787
sdMMORT| .84372*** .12968 6.51 .0000 .58956 1.09788
sdHMORT| 1.29860*** .15640 8.30 .0000 .99206 1.60515
|Covariancesof Random Parameters....................................
ACDO:CAG| 7.31338*** .52819 13.85 .0000 6.27815 8.34860
NPRS:CAG| -5.92824*** .56722 -10.45 .0000 -7.03997 -4.81651
NPRS:ACD| -4.03372*** .48360 -8.34 .0000 -4.98155 -3.08589
CERT:CAG| 1.32440*** .49298 2.69 .0072 .35818 2.29063
CERT:ACD| 1.05184*** .35871 2.93 .0034 .34879 1.75490
CERT:NPR| -.08944 .33827 -.26 .7915 -.75243 .57354
CER0:CAG| 1.29716*** .45683 2.84 .0045 .40179 2.19254
CER0:ACD| .85351*** .33054 2.58 .0098 .20566 1.50136
CER0:NPR| .07725 .30183 .26 .7980 -.51432 .66882
CERT:CER| .77115*** .20248 3.81 .0001 .37429 1.16800
MMOR:CAG| -1.71098*** .32097 -5.33 .0000 -2.34007 -1.08189
MMOR:ACD| -1.44694*** .23567 -6.14 .0000 -1.90885 -.98503
MMOR:NPR| 1.10512*** .18359 6.02 .0000 .74529 1.46494
MMOR:CER| -.24463* .12907 -1.90 .0580 -.49760 .00833
MMO0:CER| .02326 .14025 .17 .8683 -.25162 .29814
HMOR:CAG| -3.52197*** .35507 -9.92 .0000 -4.21789 -2.82605
HMOR:ACD| -2.51448*** .31284 -8.04 .0000 -3.12764 -1.90132
HMOR:NPR| 2.02189*** .23524 8.60 .0000 1.56083 2.48294
HMOR:CER| -.41736** .19544 -2.14 .0327 -.80042 -.03430
HMO0:CER| -.12152 .21660 -.56 .5748 -.54604 .30300
HMOR:MMO| .97490*** .19125 5.10 .0000 .60007 1.34974
--------+--------------------------------------------------------------------
nnnnn.D-xx or D+xx => multiply by 10 to -xx or +xx.
***, **, * ==> Significance at 1%, 5%, 10% level.
Model was estimated on Oct 27, 2022 at 09:27:18 PM
-----------------------------------------------------------------------------
--------+--------------------------------------------------------------
Cor.Mat.| CAGED ACDOORS NPRS CERT1 CERT2 MMORT HMORT
--------+--------------------------------------------------------------
CAGED| 1.00000 .93865 -.87909 .44664 .39172 -.60056 -.80319
ACDOORS| .93865 1.00000 -.87533 .51909 .37718 -.74323 -.83916
NPRS| -.87909 -.87533 1.00000 -.05100 .03944 .65585 .77961
CERT1| .44664 .51909 -.05100 1.00000 .89542 -.33017 -.36598
CERT2| .39172 .37718 .03944 .89542 1.00000 .02811 -.09542
MMORT| -.60056 -.74323 .65585 -.33017 .02811 1.00000 .88979
HMORT| -.80319 -.83916 .77961 -.36598 -.09542 .88979 1.00000
Saved Individual Estimates of WTP in matrix WTP_I [ 955x5]
Alternative Attribute Income/Cost
Chosen CAGED PRICE
Chosen ACDOORS PRICE
Chosen NPRS PRICE
Chosen CERT1 PRICE
Chosen CERT2 PRICE
(Saved absolute values. Check signs of coefficients.)
|-> ;RPL$
Error 1:Unrecognized command. (Missing ; ?)
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