[Limdep Nlogit List] Nlogit error 1085

Wed Nov 16 12:14:58 AEDT 2022

Dear Lawrence,

Thanks a lot for your reply. Yes, you are correct. I believe the error implies the same meaning. But I have double checked the dataset where the names are the same. To my understanding in the output NOTSTATDU(1), UNEMPLOYU(1) and WKDAYU(1) is implying the same variables - notstatd, unemploy and wkday for the utility function U(1) which is also indicating the constant term(b0) I used. I have no clue how to fix this. 

Regards
Sadia 

-----Original Message-----
From: Limdep <limdep-bounces at mailman.sydney.edu.au> On Behalf Of Lawrence Mwenge
Sent: Wednesday, 16 November 2022 11:50 AM
To: Limdep and Nlogit Mailing List <limdep at mailman.sydney.edu.au>
Subject: Re: [Limdep Nlogit List] Nlogit error 1085

Dear Sadia,

The Error 1085 means you variable name in the data set does not match the name you have specified in the model. To start with NOTSTATDU(1), UNEMPLOYU(1) and WKDAYU(1) are not in the model specification. But I can see notstatd, unemploy and wkday. So ensure that variable names in the dataset matches with that of the model specification.

Hint: Variable name in Nlogit takes a maximum of 8 characters.

Best wishes,
Lawrence
________________________________
From: Limdep <limdep-bounces at mailman.sydney.edu.au> on behalf of SADIA AFROZA via Limdep <limdep at mailman.sydney.edu.au>
Sent: 15 November 2022 23:54
To: limdep at limdep.itls.usyd.edu.au <limdep at limdep.itls.usyd.edu.au>
Cc: SADIA AFROZA <safroza at deakin.edu.au>
Subject: [Limdep Nlogit List] Nlogit error 1085

Dear Professor Greene and Nlogit users,

I am new to Nlogit and trying to run a RPL model. I am getting the error 1085 for several variables. Have tried removing the variables stated but the same error appears with consecutive variables. I have crosschecked the data set and codes and the variable names are the same. The model was running fine with fewer variables and similar commands. Can you please suggest how to handle this error 1085?

The error messages are:

Error   1085: Unidentified name found in VEH_TYP1

Error   1085: Unidentified name found in NOTSTATDU(1)=B0

Error   1085: Unidentified name found in UNEMPLOYU(1)=B0

Error   1085: Unidentified name found in WKDAYU(1)=B0

My commands are:

SAMPLE;All$
NLOGIT
;Lhs=sev
;Choices=0,1,2,3
;Halton
;RPL
;Pts=10
;Fcn=
a1(n),a2(n),a3(n),a4(n),a5(n),a6(n),a7(n),a8(n),a9(n),b1(n),b2(n),b3(n),b4(n),b5(n),b6(n),b7(n),b8(n),b9(n),c1(n),c2(n),c3(n),
c4(n),c5(n),c6(n),c7(n),c8(n),c9(n),d1(n),d2(n),d3(n),d4(n),d5(n),d6(n),d7(n),d8(n),d9(n)
;Model:U(0)= a0+ a1*time1+ a2*time2+ a3*time4+ a4*time5+ a5*dca2+ a6* dca3+ a7*dca4+ a8dca5+ a9*dca6+ a10*pvmt1+ a11*pvmt3+ a12*pvmt4+ a13*pvmt5+ a14(n)*pvmt6+ a15*pvmt7+ a16*pvmt8+ a17*pvmt9+ a18*pvmt10+ a19*ped_gen+ a20*dri_gen2+ a21* dri_gen3+ a22* dri_gen4+ a23*ped_age1+ a24*ped_age2+ a25*ped_age4+ a26*ped_age5+ a27* ped_age6+ a28*dri_age1+ a29*dri_age2+ a30* dri_age3+ a31* dri_age5+ a32*season1+ a33*season2+ a34*season3+ a35*light2+ a36*light3+ a37*light4+ a38*light5+ a39*atmc2+ a40*atmc3+ a41*glare1+ a42*glare2+ a43*int_typ+ a44*spd1+ a45*spd2+ a46*spd4+ a47*spd5+ a48*surfc+ a49*paved_rd+ a50*trafc2+ a51*trafc3+ a52*trafc4+ a53*trafc5+ a54*crswk_l+ a55*lanenum1+ a56*lanenum3+ a57*lanenum4+ a58*lane_w+ a59*crswk_w2+ a60*crswk_w3+ a61*divrd1+ a62*divrd2+ a63*divrd4+ a64*divrd5+ a65* sidewk+ a66* parking+ a67*tramln+ a68*bikeln+ a69*busln+ a70*slipln+ a71*shops+ a72*refarea+ a73*curvd_rd+ a74*aadt1+ a75*aadt2+ a76*aadt4+ a77*aadt5+ a78*aadt6+ a79*veh_typ1+ a80*veh_typ2+ a81*veh_typ4+ a82*veh_typ5+ a83*landuse2+ a84*landuse3+ a85*landuse4+ a86*avg_inc+ a87*avg_age+ a88*indig+ a89*gen_rat+ a90*by_train+ a91*by_bus+ a92*by_car+ a93*by_mc+ a94*by_bike+ a95*by_walk+ a96*by_multi+ a97*other+ a98*notstatd+ a99*unemploy+ a100*wkday

U(1)= b0+ b1*time1+ b2*time2+ b3*time4+ b4*time5+ b5*dca2+ b6* dca3+ b7*dca4+ b8dca5+ b9*dca6+ b10*pvmt1+ b11*pvmt3+ b12*pvmt4+ b13*pvmt5+ b14(n)*pvmt6+ b15*pvmt7+ b16*pvmt8+ b17*pvmt9+ b18*pvmt10+ b19*ped_gen+ b20*dri_gen2+ b21* dri_gen3+ b22* dri_gen4+ b23*ped_age1+ b24*ped_age2+ b25*ped_age4+ b26*ped_age5+ b27* ped_age6+ b28*dri_age1+ b29*dri_age2+ b30* dri_age3+ b31* dri_age5+ b32*season1+ b33*season2+ b34*season3+ b35*light2+ b36*light3+ b37*light4+ b38*light5+ b39*atmc2+ b40*atmc3+ b41*glare1+ b42*glare2+ b43*int_typ+ b44*spd1+ b45*spd2+ b46*spd4+ b47*spd5+ b48*surfc+ b49*paved_rd+ b50*trafc2+ b51*trafc3+ b52*trafc4+ b53*trafc5+ b54*crswk_l+ b55*lanenum1+ b56*lanenum3+ b57*lanenum4+ b58*lane_w+ b59*crswk_w2+ b60*crswk_w3+ b61*divrd1+ b62*divrd2+ b63*divrd4+ b64*divrd5+ b65* sidewk+ b66* parking+ b67*tramln+ b68*bikeln+ b69*busln+ b70*slipln+ b71*shops+ b72*refarea+ b73*curvd_rd+ b74*aadt1+ b75*aadt2+ b76*aadt4+ b77*aadt5+ b78*aadt6+ b79*veh_typ1+ b80*veh_typ2+ b81*veh_typ4+ b82*veh_typ5+ b83*landuse2+ b84*landuse3+ b85*landuse4+ b86*avg_inc+ b87*avg_age+ b88*indig+ b89*gen_rat+ b90*by_train+ b91*by_bus+ b92*by_car+ b93*by_mc+ b94*by_bike+ b95*by_walk+ b96*by_multi+ b97*other+ b98*notstatd+ b99*unemploy+ b100*wkday

U(2)= c0+ c1*time1+ c2*time2+ c3*time4+ c4*time5+ c5*dca2+ c6* dca3+ c7*dca4+ c8dca5+ c9*dca6+ c10*pvmt1+ c11*pvmt3+ c12*pvmt4+ c13*pvmt5+ c14(n)*pvmt6+ c15*pvmt7+ c16*pvmt8+ c17*pvmt9+ c18*pvmt10+ c19*ped_gen+ c20*dri_gen2+ c21* dri_gen3+ c22* dri_gen4+ c23*ped_age1+ c24*ped_age2+ c25*ped_age4+ c26*ped_age5+ c27* ped_age6+ c28*dri_age1+ c29*dri_age2+ c30* dri_age3+ c31* dri_age5+ c32*season1+ c33*season2+ c34*season3+ c35*light2+ c36*light3+ c37*light4+ c38*light5+ c39*atmc2+ c40*atmc3+ c41*glare1+ c42*glare2+ c43*int_typ+ c44*spd1+ c45*spd2+ c46*spd4+ c47*spd5+ c48*surfc+ c49*paved_rd+ c50*trafc2+ c51*trafc3+ c52*trafc4+ c53*trafc5+ c54*crswk_l+ c55*lanenum1+ c56*lanenum3+ c57*lanenum4+ c58*lane_w+ c59*crswk_w2+ c60*crswk_w3+ c61*divrd1+ c62*divrd2+ c63*divrd4+ c64*divrd5+ c65* sidewk+ c66* parking+ c67*tramln+ c68*bikeln+ c69*busln+ c70*slipln+ c71*shops+ c72*refarea+ c73*curvd_rd+ c74*aadt1+ c75*aadt2+ c76*aadt4+ c77*aadt5+ c78*aadt6+ c79*veh_typ1+ c80*veh_typ2+ c81*veh_typ4+ c82*veh_typ5+ c83*landuse2+ c84*landuse3+ c85*landuse4+ c86*avg_inc+ c87*avg_age+ c88*indig+ c89*gen_rat+ c90*by_train+ c91*by_bus+ c92*by_car+ c93*by_mc+ c94*by_bike+ c95*by_walk+ c96*by_multi+ c97*other+ c98*notstatd+ c99*unemploy+ c100*wkday

U(3)= d1*time1+ d2*time2+ d3*time4+ d4*time5+ d5*dca2+ d6* dca3+ d7*dca4+ d8dca5+ d9*dca6+ d10*pvmt1+ d11*pvmt3+ d12*pvmt4+ d13*pvmt5+ d14(n)*pvmt6+ d15*pvmt7+ d16*pvmt8+ d17*pvmt9+ d18*pvmt10+ d19*ped_gen+ d20*dri_gen2+ d21* dri_gen3+ d22* dri_gen4+ d23*ped_age1+ d24*ped_age2+ d25*ped_age4+ d26*ped_age5+ d27* ped_age6+ d28*dri_age1+ d29*dri_age2+ d30* dri_age3+ d31* dri_age5+ d32*season1+ d33*season2+ d34*season3+ d35*light2+ d36*light3+ d37*light4+ d38*light5+ d39*atmc2+ d40*atmc3+ d41*glare1+ d42*glare2+ d43*int_typ+ d44*spd1+ d45*spd2+ d46*spd4+ d47*spd5+ d48*surfc+ d49*paved_rd+ d50*trafc2+ d51*trafc3+ d52*trafc4+ d53*trafc5+  d54*lanenum1+ d55*lanenum3+ d56*lanenum4+ d57*lane_w+ d58*crswk_w2+ d59*crswk_w3+ d60*divrd1+ d61*divrd2+ d62*divrd4+ d63*divrd5+ d64* sidewk+ d65* parking+ d66*tramln+ d67*bikeln+ d68*busln+ d69*slipln+ d70*shops+ d71*refarea+ d72*curvd_rd+ d73*aadt1+ d74*aadt2+ d75*aadt4+ d76*aadt5+ d77*aadt6+ d78*veh_typ1+ d79*veh_typ2+ d80*veh_typ4+ d81*veh_typ5+ d82*landuse2+ d83*landuse3+ d84*landuse4+ d85*wkday$

Thanks and Regards

Sadia

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