Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

RE: st: RE: Replacing missing values

From   "joe J." <[email protected]>
To   [email protected]
Subject   RE: st: RE: Replacing missing values
Date   Thu, 22 Apr 2004 11:35:11 +0000

Thank you very much Nick.

From: "Nick Cox" <[email protected]>
Reply-To: [email protected]
To: <[email protected]>
Subject: RE: st: RE: Replacing missing values
Date: Thu, 22 Apr 2004 12:26:58 +0100

I can't say what would be better. Tritely,
interpolation works well when you have a few
gaps in very smooth series, and no crude
interpolation method works well otherwise.

I wrote -cipolate- on SSC partly for
a climatological problem (gaps in
temperature time series) for which -ipolate-
seemed too crude, but in practice my tests
based on omitting real data randomly and
seeing which gave the better reconstruction
did not in fact indicate much better performance
by -cipolate-. That is not very surprising
mathematically for small gaps.

I'll stress (again) for anyone listening
that -cipolate- is not a spline method.
That is, cubic interpolation is not
cubic spline interpolation.

You have to try it and see. No remote
counselling can say what is better for
your data.

[email protected]

joe J.

> Thanks Nick. True, linear interpolation is not a great idea.
> Another option
> is to regress investment series on related variables (eg.
> fuel) and time
> trend and use the fitted  values to replace missing values.
> But I think this
> would be okay if I am dealing with capital stock rather than
> investment.
> In fact I toyed with the idea of cubic interpolation, and
> wonder if the
> fluctuating character of investment decisions is a
> justification for using
> it?

*   For searches and help try:
Let your desktop sizzle! Get the hottest wallpapers. Right here at MSN Entertainment!

* For searches and help try:

© Copyright 1996–2024 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index