nmm (version 0.9)

get_start: get_start get starting values for discrete or continuous choice model.

Description

get_start get starting values for discrete or continuous choice model.

Usage

get_start(
  eq_c = NULL,
  eq_d = NULL,
  data = NULL,
  part = "joint",
  datan = "data",
  fixed_term = FALSE,
  weight_paths = TRUE,
  weight_paths_cont = FALSE,
  data_weight = NULL,
  par_c = NULL,
  par_d = NULL,
  best_method = FALSE,
  startvals = NULL,
  DEoptim_run = FALSE,
  hessian = NULL,
  transform = TRUE,
  MNtypef = "logit",
  pardogit = NULL,
  opt_method = "BFGS",
  numerical_deriv = FALSE
)

Arguments

eq_c

Continuous equations errors.

eq_d

Discrete equations.

data

data.frame is used in the optimization.

part

Type of estimation: "joint", "cont", "disc".

datan

Name of data.frame used in the optimization.

fixed_term

if TRUE, includes fixed term in log-likelihood.

weight_paths

if TRUE, weights paths of the whole system.

weight_paths_cont

if TRUE, weight paths only in continuous part.

data_weight

data.frame with weights for continuous and discrete equations, same dim as data.

par_c

Names of parameters in continuous equations.

par_d

Names of parameters in discrete equations.

best_method

if TRUE, try all possible optimization methods and choose the one with the smallest likelihood.

startvals

Starting values, can be also NULL.

DEoptim_run

if TRUE, runs DEoptim for the optimization.

hessian

Name of hessian function.

transform

if TRUE, quantile transformation is applied.

MNtypef

"dogit" or "logit".

pardogit

"dogit" parameters.

opt_method

optimization method to use.

numerical_deriv

if TRUE, numerical derivatives are calculated in nmm function

Value

Starting values for discrete or continuous blocks.

Examples

# NOT RUN {
# Example of discrete choice model
data("TravelMode", package = "AER")
eq_d <- c("ASC1 * 1 + B2_t * travel_1 + B3_v * vcost_1" ,
          "ASC2 * 1  + B2_t * travel_2 + B3_v * vcost_2",
          "ASC3 * 1  + B2_t * travel_3 + B3_v * vcost_3",
          "ASC4 * 1  + B2_t * travel_4 + B3_v * vcost_4")
parl <- c(paste0("ASC", 1:4), "B2_t", "B3_v")
obj <- get_par(parl, eq_d)

mode_spec_var <- c("wait", "vcost", "travel", "gcost")
data <- TravelMode
data$wait <- as.numeric(data$wait)
data[data$wait==0,"wait"] <- 0.000001 # add a small number to 0
data$travel <- as.numeric(data$travel)
data[data$travel==0,"travel"] <- 0.000001
data$vcost <- as.numeric(data$vcost)
data[data$vcost==0,"vcost"] <- 0.000001
data <- prepare_data(data, choice="mode", dummy="choice", PeID="individual", WeID="",
type="long", mode_spec_var =mode_spec_var, wc=FALSE)
stv <- get_start(eq_d=eq_d, data=data, datan="data", part="disc", par_d = parl, 
transform = FALSE)

#example, system of equations
data("CreditCard", package="AER")
cdat <- CreditCard
cdat$income2 <- cdat$income^2
cdat$d_selfemp <- as.numeric(cdat$selfemp)
eq_c <- c("expenditure ~  b1*age + b2*income + b3*income2",
"income ~ a1*age + a2*d_selfemp + a3*dependents + a4*majorcards")
parl <- c(paste0("b", 1:3), paste0("a", 1:4))
para_cont <- get_par(parl, eq_c)
cheqs0 <- para_cont$cheqs0
# }
# NOT RUN {
stv <- get_start(eq_c = eq_c, data=cdat, datan="cdat", part="cont", par_c=parl)
# }