Estimation the random heterogeneity model

[Valeriy]

Hello,

I tried to estimate the random heterogeneity model, and every time I got a message with error:

"The kernel appears to have died. It will restart automatically".

I don't understand where is my problem.

Can you  help me please?

Thank you.

Here you can see the my code

In [1]:

import pandas as pd
import biogeme.database as db
import biogeme.biogeme as bio
import biogeme.models as models

In [2]:

pandas = pd.read_excel("desktop\SP6ModeChoiceTLV.xlsx")
database = db.Database("SP6ModeChoiceTLV",pandas)
database.panel("ID")
from headers import *

In [3]:

ASC1 = Beta('ASC1', 0, None, None, 0)
ASC2 = Beta('ASC2', 0, None, None, 0)
ASC4 = Beta('ASC4', 0, None, None, 0)
ASC5 = Beta('ASC5', 0, None, None, 0)
ASC8 = Beta('ASC8', 0, None, None, 0)
ASC9 = Beta('ASC9', 0, None, None, 1)
Itt1 = Beta('Itt1', 0, None, None, 0)
Itt3 = Beta('Itt3', 0, None, None, 0)
ovt = Beta('ovt', 0, None, None, 0)
Cst1 = Beta('Cst1', 0, None, None, 0)
Cst3 = Beta('Cst3', 0, None, None, 0)
Cst4 = Beta('Cst4', 0, None, None, 0)
awt = Beta('awt', 0, None, None, 0)
dlay = Beta('dlay', 0, None, None, 0)
adt = Beta('adt', 0, None, None, 0)
Ott1 = Beta('Ott1', 0, None, None, 0)
Ott2 = Beta('Ott2', 0, None, None, 0)
B_Er = Beta('B_er',0,None,None,0)

In [4]:

B_RND = B_Er * bioDraws('B_RND','NORMAL')

In [5]:

V1 = ASC1 + Itt1 * binvt + ovt * bovt + Cst1 * bfare + awt * bawt + dlay * bsdpct + B_RND
V2 = ASC2 + Itt1 * binvt + ovt * bovt + Cst1 * bfare + adt * badt + dlay * bsdpct + B_RND
V4 = ASC4 + Itt1 * minvt + ovt * movt + Cst1 * mfare + awt * mawt + dlay * mdpct + B_RND
V5 = ASC5 + Itt1 * minvt + ovt * movt + Cst1 * mfare + adt * madt + dlay * mdpct + B_RND
V8 = ASC8 + Itt3 * ctime + Cst3 * cfuel + Ott1 * csrch + Ott2 * cwalk + B_RND  
V9 = ASC9 + Cst4 * cfuel + Ott1 * csrch 

In [ ]:

In [6]:

V = {1: V1, 2: V2, 4: V4, 5: V5, 8: V8, 9: V9}
av = {1: av1, 2: av2, 4: av4, 5: av5, 8: av8, 9: av9}

In [7]:

obsprob = models.logit(V,av,choice)
condprobIndiv = PanelLikelihoodTrajectory(obsprob)
logprob = log(MonteCarlo(condprobIndiv))

In [8]:

biogeme  = bio.BIOGEME(database,logprob,numberOfDraws=50)
biogeme.modelName = "SP6ModeChoiceTLV"

In [ ]:

results = biogeme.estimate(bootstrap=10)

In [ ]:

print("Results=",results)

In [ ]:

print(results)

[Ercan Kurtuluş]

It appears that you defined same error component for each alternative. You should define different error components for each alternative except for your base alternative.

10 Temmuz 2019 Çarşamba 15:55:05 UTC+3 tarihinde Valeriy yazdı: