Calculates the number of non-missing observations in a data set (X and Y).

## Syntax

**MV_OBS**(

**X**,

**Mask**,

**Y**)

- 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).

## Remarks

- In case of a missing mask input, all variables in X are considered.
- 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.
- 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.

## Files Examples

## Related Links

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

## References

- 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

## Comments

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