MV_OBS

X
is the input (explanatory) variables of the data set (two dimensional array of cells, where each column corresponds to a variable).

Mask
is the boolean array to choose the input variables in the set. If missing, all variables in X are included.

Y
is the dependent variable data set (one dimensional array of cells).

1. In case of a missing mask input, all variables in X are considered.
2. In case the number of the size of the mask array is smaller than the number of variables in X, the array is appeded with ones to match X.
3. In case the number of the size of the mask array is greater than the number of variables in X, the excess elements are dropped/ignored.

• Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
• Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740

• What to do About Missing Values in Time Series Cross-Section Data , James Honaker and Gary King, American Journal of Political Science