biogeme 3.2.6 [2020-06-02]

Python package

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

This file has automatically been generated on 2020-06-02 10:38:17.767582

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: 21probit.html
Database name: swissmetro

Estimation report

Number of estimated parameters: 3
Sample size: 2232
Excluded observations: 8496
Init log likelihood: -1547.105
Final log likelihood: -986.1888
Likelihood ratio test for the init. model: 1121.831
Rho-square for the init. model: 0.363
Rho-square-bar for the init. model: 0.361
Akaike Information Criterion: 1978.378
Bayesian Information Criterion: 1995.51
Final gradient norm: 7.3838E-03
Nbr of threads: 36
Algorithm: BFGS with trust region for simple bound constraints
Proportion analytical hessian: 0.0%
Relative projected gradient: 2.982497e-06
Number of iterations: 13
Number of function evaluations: 40
Number of gradient evaluations: 14
Number of hessian evaluations: 0
Cause of termination: Relative gradient = 3e-06 <= 6.1e-06
Optimization time: 0:00:00.038542

Estimated parameters

NameValueStd errt-testp-valueRob. Std errRob. t-testRob. p-value

Correlation of coefficients

Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value

Smallest eigenvalue: 321.491

Largest eigenvalue: 1145.47

Condition number: 3.56299