biogeme 3.1.0 [October 1, 2018]

Python package

Home page: http://biogeme.epfl.ch

Submit questions to https://groups.google.com/d/forum/biogeme

Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

This file has automatically been generated on 2018-12-27 15:30:55.945507

If you drag this HTML file into the Calc application of OpenOffice, or the spreadsheet of LibreOffice, you will be able to perform additional calculations.

Report file: 11cnl.html
Database name: swissmetro

Estimation report

Number of estimated parameters: 7
Sample size: 6768
Excluded observations: 3960
Init log likelihood: -6964.663
Final log likelihood: -5214.049
Likelihood ratio test for the init. model: 3501.228
Rho-square for the init. model: 0.251
Rho-square-bar for the init. model: 0.25
Akaike Information Criterion: 10442.1
Bayesian Information Criterion: 10489.84
Final gradient norm: 4.8282E-02
Diagnostic: b'CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL'
Database readings: 32
Iterations: 30
Data processing time: 0:00:00.000007
Optimization time: 0:00:03.690812
Nbr of threads: 8

Estimated parameters

Click on the headers of the columns to sort the table [Credits]

NameValueStd errt-testp-valueRob. Std errRob. t-testRob. p-value
ALPHA_EXISTING0.4950.028917.100.034814.20
ASC_CAR-0.2410.0384-6.263.92e-100.0534-4.56.8e-06
ASC_TRAIN0.09830.05631.740.08110.071.40.16
B_COST-0.8190.0446-18.400.059-13.90
B_TIME-0.7770.0558-13.900.102-7.593.29e-14
MU_EXISTING2.520.17514.400.24810.10
MU_PUBLIC4.110.5697.234.73e-130.4978.282.22e-16

Correlation of coefficients

Click on the headers of the columns to sort the table [Credits]

Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
ASC_CARALPHA_EXISTING0.0003920.353-18.800.0008090.436-14.90
ASC_TRAINALPHA_EXISTING-0.000985-0.604-5.132.89e-07-0.00103-0.422-4.391.12e-05
ASC_TRAINASC_CAR0.000650.35.854.89e-090.001630.4365.054.34e-07
B_COSTALPHA_EXISTING-0.000393-0.305-21.90-0.000767-0.374-16.70
B_COSTASC_CAR-0.000103-0.0601-9.540-0.000832-0.264-6.471.01e-10
B_COSTASC_TRAIN0.001040.413-16.500.0008680.21-11.30
B_TIMEALPHA_EXISTING-0.000439-0.272-18.30-0.00137-0.385-10.60
B_TIMEASC_CAR-0.00132-0.614-6.312.77e-10-0.00454-0.829-3.580.000342
B_TIMEASC_TRAIN-0.000275-0.0875-10.60-0.0028-0.39-6.041.52e-09
B_TIMEB_COST0.001150.460.7950.4260.003070.5090.4770.633
MU_EXISTINGALPHA_EXISTING-0.000948-0.18811.10-0.000534-0.06187.991.33e-15
MU_EXISTINGASC_CAR-0.00258-0.38514.30-0.00353-0.26610.30
MU_EXISTINGASC_TRAIN0.001690.17213.900.004910.28210.10
MU_EXISTINGB_COST0.003610.4642100.005670.38714.40
MU_EXISTINGB_TIME0.006540.6712300.008550.336140
MU_PUBLICALPHA_EXISTING-0.00763-0.4646.215.3e-10-0.0124-0.7186.934.3e-12
MU_PUBLICASC_CAR0.001060.04837.661.82e-14-0.00845-0.3188.430
MU_PUBLICASC_TRAIN0.0230.7197.583.44e-140.01570.4518.550
MU_PUBLICB_COST0.009420.3718.9100.01320.44910.40
MU_PUBLICB_TIME0.00680.2148.7400.0230.45310.60
MU_PUBLICMU_EXISTING0.01520.1532.810.004950.02930.2373.20.00139

Smallest eigenvalue: 3.06149

Smallest singular value: 3.06149