Error in estimating MDCEV model with RP&SP data
Posted: 17 Feb 2023, 18:08
Dear Sir,
For my research work, I need to develop models with pooled RP&SP data. Considering this, I wrote a code for the MDCEV model with RP & SP data.
To practice and learn the codes, I have utilized the data from the MDCEV model (without outside good) and RP SP MNL model from Apollo examples.
Actually, I have added four more attributes (RP, SP, RP Journey, and SP task) to the MDCEV data.
However, I am getting the following error during model estimation: Error in apollo_preprocess(mdcev_settings, modelType, functionality, apollo_inputs) :
"continuousChoice" for model component "MDCEV" should be a list of numerical vectors, each with as many rows as observations..
I would request you to please suggest on how can I fix this code. I am using apollo version 0.2.8.
My code is as follows:
For my research work, I need to develop models with pooled RP&SP data. Considering this, I wrote a code for the MDCEV model with RP & SP data.
To practice and learn the codes, I have utilized the data from the MDCEV model (without outside good) and RP SP MNL model from Apollo examples.
Actually, I have added four more attributes (RP, SP, RP Journey, and SP task) to the MDCEV data.
However, I am getting the following error during model estimation: Error in apollo_preprocess(mdcev_settings, modelType, functionality, apollo_inputs) :
"continuousChoice" for model component "MDCEV" should be a list of numerical vectors, each with as many rows as observations..
I would request you to please suggest on how can I fix this code. I am using apollo version 0.2.8.
My code is as follows:
Code: Select all
# ################################################################# #
#### LOAD LIBRARY AND DEFINE CORE SETTINGS ####
# ################################################################# #
### Clear memory
rm(list = ls())
### Load Apollo library
library(apollo)
### Initialise code
apollo_initialise()
### Set core controls
apollo_control = list(
modelName = "MDCEV_RP_SP",
modelDescr = "MDCEV model using RP and SP data",
indivID = "indivID",
outputDirectory = "output"
)
# ################################################################# #
#### LOAD DATA AND APPLY ANY TRANSFORMATIONS ####
# ################################################################# #
database = read.csv("MDCEV_RP_SP_Dummy.csv")
# ################################################################# #
#### DEFINE MODEL PARAMETERS ####
# ################################################################# #
### Vector of parameters, including any that are kept fixed in estimation
apollo_beta = c(alpha_base = 0,
gamma_dropOff = 1,
gamma_work = 1,
gamma_school = 1,
gamma_shopping = 1,
gamma_privBusiness = 1,
gamma_petrol = 1,
gamma_leisure = 1,
gamma_vacation = 1,
gamma_exercise = 1,
gamma_home = 1,
gamma_travel = 1,
gamma_other = 1,
delta_dropOff = 0,
delta_work = 0,
delta_school = 0,
delta_shopping = 0,
delta_privBusiness = 0,
delta_petrol = 0,
delta_leisure = 0,
delta_vacation = 0,
delta_exercise = 0,
delta_home = 0,
delta_travel = 0,
delta_other = 0,
delta_female = 0,
delta_age_above_30 = 0,
mu_RP = 1,
mu_SP = 1,
sig = 1)
### 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("delta_home", "sig", "mu_RP")
# ################################################################# #
#### GROUP AND VALIDATE INPUTS ####
# ################################################################# #
apollo_inputs = apollo_validateInputs()
# ################################################################# #
#### DEFINE MODEL AND LIKELIHOOD FUNCTION ####
# ################################################################# #
apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
### 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()
### Define individual alternatives
alternatives = c("dropOff",
"work",
"school",
"shopping",
"privBusiness",
"petrol",
"leisure",
"vacation",
"exercise",
"home",
"travel",
"other")
### Define availabilities
avail = list(dropOff = 1,
work = 1,
school = 1,
shopping = 1,
privBusiness = 1,
petrol = 1,
leisure = 1,
vacation = 1,
exercise = 1,
home = 1,
travel = 1,
other = 1)
### Define continuous consumption for individual alternatives
continuousChoice = list(dropOff = t_a01/60,
work = t_a02/60,
school = t_a03/60,
shopping = t_a04/60,
privBusiness = t_a05/60,
petrol = t_a06/60,
leisure = t_a07/60,
vacation = t_a08/60,
exercise = t_a09/60,
home = t_a10/60,
travel = t_a11/60,
other = t_a12/60)
### Define utilities for individual alternatives
V = list()
V[["dropOff" ]] = delta_dropOff + delta_female*female
V[["work" ]] = delta_work + delta_female*female + delta_age_above_30*age
V[["school" ]] = delta_school
V[["shopping"]] = delta_shopping + delta_female*female
V[["privBusiness"]] = delta_privBusiness + delta_female*female
V[["petrol" ]] = delta_petrol
V[["leisure" ]] = delta_leisure + delta_age_above_30*age
V[["vacation"]] = delta_vacation
V[["exercise"]] = delta_exercise + delta_female*female + delta_age_above_30*age
V[["home" ]] = delta_home
V[["travel" ]] = delta_travel
V[["other" ]] = delta_other
### Define alpha parameters
alpha = list(dropOff = 1 /(1 + exp(-alpha_base)),
work = 1 /(1 + exp(-alpha_base)),
school = 1 /(1 + exp(-alpha_base)),
shopping = 1 /(1 + exp(-alpha_base)),
privBusiness = 1 /(1 + exp(-alpha_base)),
petrol = 1 /(1 + exp(-alpha_base)),
leisure = 1 /(1 + exp(-alpha_base)),
vacation = 1 /(1 + exp(-alpha_base)),
exercise = 1 /(1 + exp(-alpha_base)),
home = 1 /(1 + exp(-alpha_base)),
travel = 1 /(1 + exp(-alpha_base)),
other = 1 /(1 + exp(-alpha_base)))
### Define gamma parameters
gamma = list(dropOff = gamma_dropOff,
work = gamma_work,
school = gamma_school,
shopping = gamma_shopping,
privBusiness = gamma_privBusiness,
petrol = gamma_petrol,
leisure = gamma_leisure,
vacation = gamma_vacation,
exercise = gamma_exercise,
home = gamma_home,
travel = gamma_travel,
other = gamma_other)
### Define costs for individual alternatives
cost = list(dropOff = 1,
work = 1,
school = 1,
shopping = 1,
privBusiness = 1,
petrol = 1,
leisure = 1,
vacation = 1,
exercise = 1,
home = 1,
travel = 1,
other = 1)
### Compute probabilities for the RP part of the data using MDCEV model
mdcev_settings_RP = list(
alternatives = alternatives,
avail = avail,
continuousChoice = continuousChoice,
alpha = alpha,
gamma = gamma,
sigma = sig,
cost = cost,
budget = 24,
utilities = list(dropOff = mu_RP*V[["dropOff"]],
work = mu_RP*V[["work"]],
school = mu_RP*V[["school"]],
privBusiness = mu_RP*V[["privBusiness"]],
petrol = mu_RP*V[["petrol"]],
leisure = mu_RP*V[["leisure"]],
vacation = mu_RP*V[["vacation"]],
exercise = mu_RP*V[["exercise"]],
home = mu_RP*V[["home"]],
travel = mu_RP*V[["travel"]],
other = mu_RP*V[["other"]]),
rows = (RP==1)
)
P[["RP"]] = apollo_mdcev(mdcev_settings_RP, functionality)
### Compute probabilities for the SP part of the data using MDCEV model
mdcev_settings_SP = list(
alternatives = alternatives,
avail = avail,
continuousChoice = continuousChoice,
alpha = alpha,
gamma = gamma,
sigma = sig,
cost = cost,
budget = 24,
utilities = list(dropOff = mu_SP*V[["dropOff"]],
work = mu_SP*V[["work"]],
school = mu_SP*V[["school"]],
privBusiness = mu_SP*V[["privBusiness"]],
petrol = mu_SP*V[["petrol"]],
leisure = mu_SP*V[["leisure"]],
vacation = mu_SP*V[["vacation"]],
exercise = mu_SP*V[["exercise"]],
home = mu_SP*V[["home"]],
travel = mu_SP*V[["travel"]],
other = mu_SP*V[["other"]]),
rows = (SP==1)
)
P[["SP"]] = apollo_mdcev(mdcev_settings_RP, functionality)
### Combined model
P = apollo_combineModels(P, apollo_inputs, functionality)
### Take product across observation for same individual
P = apollo_panelProd(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)
# ################################################################# #
#### MODEL OUTPUTS ####
# ################################################################# #
# ----------------------------------------------------------------- #
#---- FORMATTED OUTPUT (TO SCREEN) ----
# ----------------------------------------------------------------- #
apollo_modelOutput(model)