Latent class model for panel data

[Marie Duper]

Hi

I am making a model for panel data (flat panel data). I want to also do latent class analysis. I have been following the example on: 

https://biogeme.epfl.ch/sphinx/auto_examples/swissmetro/plot_b16panel_discrete_socio_eco.html#

1) I do get estimates but I cannot understand what they mean. In the example above what is ASC_SM_S_class0 and ASC_SM_S_class1? What are 

CLASS_CTE and CLASS_INC? 

2) If I were to add other SE factors would it look like: 

W = CLASS_CTE + Class_Gender*Gender + Class_Race*Race

3) Why are the parameters for class 0 set to 0?

4) I want to get the class probabilities. I am trying to follow

https://biogeme.epfl.ch/sphinx/auto_examples/swissmetro/plot_b13panel_simul.html

But I cannot get it to work.

simulated_loglike = logprob.getValue_c(

database=flat_database,

betas=results.getBetaValues(),

numberOfDraws=250,

aggregation=True,

prepareIds=True,

)

numerator = MonteCarlo(ACS2_param[0] * probIndiv)

denominator = MonteCarlo(probIndiv)

simulate = {

'Numerator': numerator,

'Denominator': denominator,

}

biosim = bio.BIOGEME(flat_database, simulate)

biosim.modelName = 'panel_flat_latent_class_individual_sim'

class_simulation = biosim.simulate(theBetaValues=results.getBetaValues())

class_simulation.describe()

Thank you