Error when estimating a ICLV model with two sources of information

[cbobcat]

Hi, I am getting the same error when running models with multiple data sources. I'm using Apollo version 0.3.1. Running on one core works, but increasing the number of cores to 2 (or more) results in this:

Testing influence of parameters
Error in checkForRemoteErrors(lapply(cl, recvResult)) :
one node produced an error: (subscript) logical subscript too long

Has there been any progress on this issue since the last posts?


Posting the code below:

library(apollo)
apollo_initialise()

apollo_control = list(
modelName ="MMNL alt-specific combined indic",
modelDescr ="Mixed logit with combined indicators, scale normalization",
indivID ="RespID",
mixing = TRUE,
nCores = 1,
outputDirectory = "output",
panelData = TRUE
)

database = read.csv("Data_clean.csv", header=TRUE, sep=";")

database = subset(database,database$avail == 1)

apollo_beta = c( asc_m = -0.893299,
asc_r = -1.249897,
asc_opt = 0,
b_comp_mu = 0.156941,
b_comp_sig = 0,
b_m_single_thresh_mu = -0.295765,
b_m_single_thresh_sig = 0,
b_m_stepped_thresh_mu = -0.121848,
b_m_stepped_thresh_sig = 0,
b_m_no_thresh = 0,
b_r_single_thresh_mu = -0.441755,
b_r_single_thresh_sig = 0,
b_r_stepped_thresh_mu = -0.01,
b_r_stepped_thresh_sig = 0,
b_r_no_thresh = 0,
b_sched_start = 0,
b_sched_end_mu = -0.243476,
b_sched_end_sig = 0,
b_sched_install_mu = 0.206316,
b_sched_install_sig = 0,
b_m_mr_owner_mu = 0.051143,
b_m_mr_owner_sig = 0,
b_m_mr_exam = 0,
b_m_mr_consult_mu = 0.056611,
b_m_mr_consult_sig = 0,
b_r_mr_owner_mu = 0,
b_r_mr_owner_sig = 0,
b_r_mr_exam = 0,
b_r_mr_consult_mu = 0.116185,
b_r_mr_consult_sig = 0,
mu_beetlesDK = 1,
mu_birdsDK = 1,
mu_plantsDK = 1,
mu_beetlesFI = 1,
mu_birdsFI = 1,
mu_plantsFI = 1)

apollo_fixed = c("asc_opt", "b_m_no_thresh", "b_r_no_thresh", "b_sched_start", "b_m_mr_exam", "b_r_mr_exam", "mu_beetlesDK")

apollo_draws = list(
interDrawsType = "mlhs",
interNDraws = 500,
interNormDraws = c("draws_comp","draws_m_single_thresh","draws_r_single_thresh","draws_m_stepped_thresh","draws_r_stepped_thresh","draws_sched_end","draws_sched_install","draws_m_mr_owner","draws_r_mr_owner","draws_m_mr_consult","draws_r_mr_consult")
)

apollo_randCoeff = function(apollo_beta, apollo_inputs){
randcoeff = list()

randcoeff[["b_comp"]] = exp(b_comp_mu + b_comp_sig * draws_comp) # lognormal distr
randcoeff[["b_m_single_thresh"]] = b_m_single_thresh_mu + b_m_single_thresh_sig * draws_m_single_thresh
randcoeff[["b_m_stepped_thresh"]] = b_m_stepped_thresh_mu + b_m_stepped_thresh_sig * draws_m_stepped_thresh
randcoeff[["b_r_single_thresh"]] = b_r_single_thresh_mu + b_r_single_thresh_sig * draws_r_single_thresh
randcoeff[["b_r_stepped_thresh"]] = b_r_stepped_thresh_mu + b_r_stepped_thresh_sig * draws_r_stepped_thresh
randcoeff[["b_sched_end"]] = b_sched_end_mu + b_sched_end_sig * draws_sched_end
randcoeff[["b_sched_install"]] = b_sched_install_mu + b_sched_install_sig * draws_sched_install
randcoeff[["b_m_mr_owner"]] = b_m_mr_owner_mu + b_m_mr_owner_sig * draws_m_mr_owner
randcoeff[["b_r_mr_owner"]] = b_r_mr_owner_mu + b_r_mr_owner_sig * draws_r_mr_owner
randcoeff[["b_m_mr_consult"]] = b_m_mr_consult_mu + b_m_mr_consult_sig * draws_m_mr_consult
randcoeff[["b_r_mr_consult"]] = b_r_mr_consult_mu + b_r_mr_consult_sig * draws_r_mr_consult

return(randcoeff)
}

apollo_inputs = apollo_validateInputs()

apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){

apollo_attach(apollo_beta, apollo_inputs)
on.exit(apollo_detach(apollo_beta, apollo_inputs))

# Create list of probabilities P
P = list()

V = list()
V[['alt_m']] = asc_m + b_comp * (m_comp/10000) + b_m_single_thresh * (m_thresh == 2) + b_m_stepped_thresh * (m_thresh == 1) + b_m_no_thresh * (m_thresh == 0) + b_sched_start * (m_sched == 0) + b_sched_end * (m_sched == 2) + b_sched_install * (m_sched == 1) + b_m_mr_owner * (m_mr == 1) + b_m_mr_exam * (m_mr == 0) + b_m_mr_consult * (m_mr == 2)
V[['alt_r']] = asc_r + b_comp * (r_comp/10000) + b_r_single_thresh * (r_thresh == 2) + b_r_stepped_thresh * (r_thresh == 1) + b_r_no_thresh * (r_thresh == 0) + b_sched_start * (r_sched == 0) + b_sched_end * (r_sched == 2) + b_sched_install * (r_sched == 1) + b_r_mr_owner * (r_mr == 1) + b_r_mr_exam * (r_mr == 0) + b_r_mr_consult * (r_mr == 2)
V[['optout']] = asc_opt


mnl_settings_beetlesDK = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_beetlesDK*V[["alt_m"]],
alt_r = mu_beetlesDK*V[["alt_r"]],
optout = mu_beetlesDK*V[["optout"]]),
rows = (beetlesDK==1)
)
P[["beetlesDK"]] = apollo_mnl(mnl_settings_beetlesDK, functionality)


mnl_settings_plantsDK = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_plantsDK*V[["alt_m"]],
alt_r = mu_plantsDK*V[["alt_r"]],
optout = mu_plantsDK*V[["optout"]]),
rows = (plantsDK==1)
)
P[["plantsDK"]] = apollo_mnl(mnl_settings_plantsDK, functionality)


mnl_settings_birdsDK = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_birdsDK*V[["alt_m"]],
alt_r = mu_birdsDK*V[["alt_r"]],
optout = mu_birdsDK*V[["optout"]]),
rows = (birdsDK==1)
)
P[["birdsDK"]] = apollo_mnl(mnl_settings_birdsDK, functionality)


mnl_settings_beetlesFI = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_beetlesFI*V[["alt_m"]],
alt_r = mu_beetlesFI*V[["alt_r"]],
optout = mu_beetlesFI*V[["optout"]]),
rows = (beetlesFI==1)
)
P[["beetlesFI"]] = apollo_mnl(mnl_settings_beetlesFI, functionality)


mnl_settings_birdsFI = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_birdsFI*V[["alt_m"]],
alt_r = mu_birdsFI*V[["alt_r"]],
optout = mu_birdsFI*V[["optout"]]),
rows = (birdsFI==1)
)
P[["birdsFI"]] = apollo_mnl(mnl_settings_birdsFI, functionality)


mnl_settings_plantsFI = list(
alternatives = c(alt_m = 1, alt_r = 2, optout = 0),
choiceVar = choice,
utilities = list(alt_m = mu_plantsFI*V[["alt_m"]],
alt_r = mu_plantsFI*V[["alt_r"]],
optout = mu_plantsFI*V[["optout"]]),
rows = (plantsFI==1)
)
P[["plantsFI"]] = apollo_mnl(mnl_settings_plantsFI, functionality)


P = apollo_combineModels(P, apollo_inputs, functionality)

P = apollo_panelProd(P, apollo_inputs, functionality)

P = apollo_avgInterDraws(P, apollo_inputs, functionality)

# Prepare and return outputs of function
P = apollo_prepareProb(P, apollo_inputs, functionality)
return(P)
}

model = apollo_estimate(apollo_beta, apollo_fixed, apollo_probabilities, apollo_inputs)

apollo_modelOutput(model, modelOutput_settings=list(printPVal = TRUE))

[stephanehess]

Hi

can you share your code and data with me outside the forum and I'll look into it

Stephane