ApolloChoiceModelling forum

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apollo_initialise()

### Set core controls
apollo_control = list(
  modelName ="car_purchase_mxl",
  modelDescr ="Mixed logit model on Train's car purchase data",
  indivID   ="ID",  
  mixing    = TRUE, 
  nCores    = 1 ## here is the trouble maker
)

# ################################################################# #
#### LOAD DATA AND APPLY ANY TRANSFORMATIONS                     ####
# ################################################################# #
data("Car") ### load data from mlogit() package
Car$ID      = 1:nrow(Car)
Car$Choice  = as.numeric(substring(Car$choice, 7))
database = Car

# ################################################################# #
#### ANALYSIS OF CHOICES                                         ####
# ################################################################# #

choiceAnalysis_settings <- list(
  alternatives = c(car1=1, car2=2,car3=3,car4=4,car5=5, car6=6),
  avail        = 1,
  explanators  = database[,c("college","hsg2","coml5")],
  choiceVar    = database$Choice
  #rows         = database$income>30000
)

apollo_choiceAnalysis(choiceAnalysis_settings, apollo_control, database)

# ################################################################# #
#### DEFINE MODEL PARAMETERS                                     ####
# ################################################################# #

### Vector of parameters, including any that are kept fixed in estimation
apollo_beta = c(priceLogInc    = 0,
                range          = 0,
                mu_log_b_oc    = 0,
                sigma_log_b_oc = -2,
                meth           = 0,
                cng            = 0,
                mu_b_ev        = 0,
                sigma_b_ev     = -2,
                truck          = 0,
                mu_b_suv       = 0,
                sigma_b_suv    = -2,
                van            = 0
                )

### Vector with names (in quotes) of parameters to be kept fixed at their starting value in apollo_beta, use apollo_beta_fixed = c() if none
apollo_fixed = c()

# ################################################################# #
#### DEFINE RANDOM COMPONENTS                                    ####
# ################################################################# #

### Set parameters for generating draws
apollo_draws = list(
 interDrawsType = "halton",
 interNDraws    = 0,
 interUnifDraws = c(),
 interNormDraws = c(),
 intraDrawsType = "halton",
 intraNDraws    = 10,
 intraUnifDraws = c(),
 intraNormDraws = c("draws_oc", "draws_ev", "draws_suv")
)

### Create random parameters
apollo_randCoeff = function(apollo_beta, apollo_inputs){
  randcoeff = list()

  randcoeff[["opcost"]] = -exp( mu_log_b_oc + sigma_log_b_oc * draws_oc )
  randcoeff[["ev"]]     =  mu_b_ev + sigma_b_ev * draws_oc 
  randcoeff[["suv"]]    =  mu_b_suv + sigma_b_suv * draws_suv 

  return(randcoeff)
}

# ################################################################# #
#### GROUP AND VALIDATE INPUTS                                   ####
# ################################################################# #

apollo_inputs = apollo_validateInputs()

# ################################################################# #
#### DEFINE MODEL AND LIKELIHOOD FUNCTION                        ####
# ################################################################# #

apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
  
  ### Function initialisation: do not change the following three commands
  ### Attach inputs and detach after function exit
  apollo_attach(apollo_beta, apollo_inputs)
  on.exit(apollo_detach(apollo_beta, apollo_inputs))
  
  ### Create list of probabilities P
  P = list()
  
  ### List of utilities: these must use the same names as in mnl_settings, order is irrelevant
  V = list()
  V[['car1']] = suv * (type1 == "sportuv") + truck * (type1 == "truck") + van * (type1 == "van") + meth * (fuel1 == "methanol") + cng * (fuel1 == "cng") + ev * (fuel1 == "electric") + priceLogInc * price1 + range * range1 + opcost * cost1 
  V[['car2']] = suv * (type2 == "sportuv") + truck * (type2 == "truck") + van * (type2 == "van") + meth * (fuel2 == "methanol") + cng * (fuel2 == "cng") + ev * (fuel2 == "electric") + priceLogInc * price2 + range * range2 + opcost * cost2
  V[['car3']] = suv * (type3 == "sportuv") + truck * (type3 == "truck") + van * (type3 == "van") + meth * (fuel3 == "methanol") + cng * (fuel3 == "cng") + ev * (fuel3 == "electric") + priceLogInc * price3 + range * range3 + opcost * cost3
  V[['car4']] = suv * (type4 == "sportuv") + truck * (type4 == "truck") + van * (type4 == "van") + meth * (fuel4 == "methanol") + cng * (fuel4 == "cng") + ev * (fuel4 == "electric") + priceLogInc * price4 + range * range4 + opcost * cost4
  V[['car5']] = suv * (type5 == "sportuv") + truck * (type5 == "truck") + van * (type5 == "van") + meth * (fuel5 == "methanol") + cng * (fuel5 == "cng") + ev * (fuel5 == "electric") + priceLogInc * price5 + range * range5 + opcost * cost5
  V[['car6']] = suv * (type6 == "sportuv") + truck * (type6 == "truck") + van * (type6 == "van") + meth * (fuel6 == "methanol") + cng * (fuel6 == "cng") + ev * (fuel6 == "electric") + priceLogInc * price6 + range * range6 + opcost * cost6
  
  ### Define settings for MNL model component
  mnl_settings    = list(
    alternatives  = c(car1=1, car2=2, car3=3, car4=4, car5=5, car6=6),
    avail         = 1,
    choiceVar     = Choice,
    V             = V
  )
  
  
  ### Compute probabilities using MNL model
  P[['model']] = apollo_mnl(mnl_settings, functionality)
  
  ### Take product across observation for same individual
  #P = apollo_panelProd(P, apollo_inputs, functionality)
  
  ### Average across intra-individual draws
  P = apollo_avgIntraDraws(P, apollo_inputs, functionality)
  
  ### Prepare and return outputs of function
  P = apollo_prepareProb(P, apollo_inputs, functionality)
  return(P)
}

# ################################################################# #
#### MODEL ESTIMATION                                            ####
# ################################################################# #

model = apollo_estimate(apollo_beta, apollo_fixed,
                        apollo_probabilities, apollo_inputs, 
                        estimate_settings=list(hessianRoutine="maxLik"))

# ################################################################# #
#### MODEL OUTPUTS                                               ####
# ################################################################# #

# ----------------------------------------------------------------- #
#---- FORMATTED OUTPUT (TO SCREEN)                               ----
# ----------------------------------------------------------------- #

apollo_modelOutput(model)

Code: Select all

Attempting to split data into 4 pieces.
 Number of observations per worker (thread):
  1164, 1164, 1164, 1162
 Writing pieces to disk.... Done. 248.6MB of RAM in use.
Preparing workersError in makePSOCKcluster(names = spec, ...) : 
  Cluster setup failed. 4 of 4 workers failed to connect.