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st: RE: rowskew?

From   "Matt Spittal" <[email protected]>
To   <[email protected]>
Subject   st: RE: rowskew?
Date   Tue, 14 Oct 2008 14:21:41 +1100


You can use the moments about the mean to calculate skew and kurtosis for a row of variables.  Imagine that you want to do this for the variables weight, length and price from the auto dataset.  
	sysuse auto, clear

	// get mean and N
	egen rowmean = rowmean(weight length price)
	egen rowN = rownonmiss(weight length price)

	// calculate 2, 3, and 4th moments about the mean
	gen m2 = 1/rowN * ((weight - rowmean)^2 + (length - rowmean)^2 + (price - rowmean)^2)
	gen m3 = 1/rowN * ((weight - rowmean)^3 + (length - rowmean)^3 + (price - rowmean)^3) 
	gen m4 = 1/rowN * ((weight - rowmean)^4 + (length - rowmean)^4 + (price - rowmean)^4)

	// calculate skew and kurtosis
	gen rowskew = m3*m2^(-3/2)
	gen rowkurt = m4*m2^(-2)

	list weight length price rowskew rowkurt in 1/10

-- Matt
[email protected]	

-----Original Message-----
From: [email protected]
[mailto:[email protected]]On Behalf Of jeheyman
Sent: Tuesday, 14 October 2008 12:31 PM
To: [email protected]
Subject: st: rowskew?

Is it possible to calculate essentially a rowskew and rowkurtosis in  
the same way that egen calculates rowmean?

For each observation I have 18 variables and I need, obviously, the  
three distribution measures.  Mean is trivial but the other two are  
proving elusive. I feel like I'm overlooking something obvious and  
posting seemed to be better than continuing to bang my head against  
the wall.


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