'X' as an array of at least two dimensions - r

Question

Very new to R and RStudio and the whole concept of coding language. I'm trying to create reproducible code so I can properly ask a question.
The first error says:
Error in colSums(cTrain * log(pTrain) + cCar * log(pCar) + cSM * log(pSM)) :
'x' must be an array of at least two dimensions
Using this code, where can I fix this so that 'x' can have two dimensions?
mydata <- structure(list(LUGGAGE=c(0,1,0,1,0), GA=c(0,0,0,0,0), TRAIN_AV=c(1,1,1,1,1), CAR_AV=c(1,1,1,1,1), SM_AV=c(1,1,1,1,1),
TRAIN_TT=c(114,142,235,193,227), TRAIN_CO=c(40,109,124,90,94),
SM_TxT=c(44,91,179,119,108), SM_CO=c(46,132,132,127,118),
CAR_TT=c(140,110,170,150,286), CAR_CO=c(123,104,80,95,169), CHOICE=c(2,2,3,3,2)),
.Names=c("Luggage","GA","TRAIN_AV","CAR_AV","SM_AV","TRAIN_TT","TRAIN_CO","SM_TT","SM_CO","CAR_TT","CAR_CO","CHOICE"),
row.names=c(NA,5L), class="data.frame")
## Initial value of parameters
initPar <- 8
### Log-Likelihood Function of the Logit Model
library("maxLik")
loglik <- function(x) {
## Parameters
# Alternative Specific Constants
asc_train <- x[1]
asc_sm <- x[2]
# Travel Time to Destination
ttime <- x[3]
# Travel Cost to Destination
tcost_train <- x[4]
tcost_car <- x[5]
tcost_sm <- x[6]
# Effect of Swiss Annual Season Ticket
ga <- x[7]
# Effect of luggage
luggage <- x[8]
## Log-Likelihood Variable
LL = 0
## Utility Function Vin
train <- asc_train*matrix(1, nrow=nrow(mydata), ncol = 1) + tcost_train*mydata$TRAIN_CO + ttime*mydata$TRAIN_TT/100 + ga*mydata$GA + luggage*mydata$LUGGAGE
car <- tcost_car*mydata$CAR_CO + ttime*mydata$CAR_TT/100 + luggage*mydata$LUGGAGE
sm <- asc_sm*matrix(1, nrow=nrow(mydata), ncol = 1) + tcost_sm*mydata$SM_CO + ttime*mydata$SM_TT/100 + ga*mydata$GA + luggage*mydata$LUGGAGE
## exp(Vin) and Control for Mode Availability
train <- mydata$TRAIN_AV *exp(train)
car <- mydata$CAR_AV *exp(car)
sm <- mydata$SM_AV *exp(sm)
## Choice Probabilities
deno <- (train + car + sm)
## Individual Choice Probabilities
pTrain <- mydata$TRAIN_AV *(train / deno)
pCar <- mydata$CAR_AV *(car / deno)
pSM <- mydata$SM_AV *(sm / deno)
pTrain <- (pTrain!=0) *pTrain + (pTrain==0)
pCar <- (pCar!=0) *pCar + (pCar==0)
pSM <- (pSM!=0) *pSM + (pSM==0)
## Choice Results
cTrain <- mydata$CHOICE == "1"
cCar <- mydata$CHOICE == "3"
cSM <- mydata$CHOICE == "2"
## Log-Likelihood Function
LL <- colSums(cTrain*log(pTrain) + cCar*log(pCar) + cSM*log(pSM))
}
### Maximization of Log-Likelihood Function ###
# Parameter Optimization
result <- maxLik(loglik, start=numeric(initPar))
# Parameter Estimation, Hessian Matrix Calculation
parameters <- result$estimate
hessianMatrix <- result$hessian
# T-Statistic Calculation
tval <- parameters/sqrt(-diag(solve(hessianMatrix)))
# L(0), Log-Likelihood When All parameters = 0
L0 <- loglik(numeric(initPar))
# LL, Maximumum Likelihood
LL <- result$maximum

Answer 1

Nicely asked question with a reproducible example; upvoted!
Your problem was very simple. Your function looks for a variable called mydata$LUGGAGE that doesn't exist. R is case sensitive and your column is called mydata$Luggage.
All you have to do is
names(mydata)[1] <- "LUGGAGE"
Now run your script and you should get this result:
result <- maxLik(loglik, start=numeric(initPar))
result
# Maximum Likelihood estimation
# Newton-Raphson maximisation, 30 iterations
# Return code 2: successive function values within tolerance limit
# Log-Likelihood: -1.744552e-07 (8 free parameter(s))
# Estimate(s): -277.7676 -250.6531 8.651811 -1.680196 -4.208955 -1.281697 0 354.4692