arima method in mtsdi - r

Question

I have a large data set(more than 2000 rows and 2000 variables) with lots of missing values. I am using mnimputfunction of mtsdi package of R for imputing all missing values. This is my code
formula = data
imput_out <- mnimput(formula,data, by = NULL, log = FALSE, log.offset = 1,
eps = 1e-3, maxit = 1e2, ts = TRUE, method = "arima", ar.control = list(order = c(1,1,1), period = 4, f.eps = 1e-6, f.maxit = 1e3, ga.bf.eps = 1e-6,verbose = TRUE, digits = getOption("digits")))
But I am getting an error
Error in o[1:3, j] : incorrect number of dimensions
Please help me out.

Answer 1

you have to get real deep into the package source to uncover whats going on here.
the ar.control is placed into a variable o that is iterated on by the j # of columns that you put into your formula. so if your formula looks like ~c31+c32+c33 your ar term need to be 3 columns of (p,d,q) values
I assigned it outside of the ar.control parameter for ease of editing
arcontrol<-list(order=cbind(c(1,0,0),c(0,0,1),c(1,0,0)), period=NULL)
mnimput(formula,data,eps=1e-3,ts=TRUE, method="arima", ar.control=arcontrol
here is the package source if you are interested
function (xn, o, s, eps, maxit)
{
rows <- dim(xn)[1]
cols <- dim(xn)[2]
models <- as.list(rep(NA, cols))
ar.pred <- matrix(NA, nrow = rows, ncol = cols)
for (j in 1:cols) {
if (is.null(s)) {
order <- o[1:3, j]
seasonal <- list(order = c(0, 0, 0), period = NA)
}
else {
order <- o[1:3, j]
seasonal <- list(order = o[4:6, j], period = s)
}
models[[j]] <- arima(xn[, j], order = order, seasonal = seasonal,
xreg = NULL, optim.control = list(maxit = maxit,
reltol = eps))
ar.pred[, j] <- xn[, j] - residuals(models[[j]])
}
retval <- list(ar.pred = ar.pred, models = models)
return(retval)
}