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From |
Austin Nichols <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Weighted Euclidean distances with panel data |

Date |
Wed, 9 Sep 2009 14:56:46 -0400 |

James Cross<[email protected]>: You are just computing a quadratic form, with weights on the diagonal of a weighting matrix, which you can do in a number of ways. Until you specify how to treat missing values and where the weights come from, it is hard to offer specific advice. But try: clear input prop i a p r 00032 1 1 100 0 00032 2 1 50 1 00032 3 1 100 100 00032 4 1 100 0 end g diff=p-r mkmat diff, mat(x) mat A=I(4) mat d=x'*A*x g d=(p-r)^2 egen wd=sum(d), by(a) qui reshape wide p r d*, i(a) j(i) g red=(p1-r1)^2+(p2-r2)^2+(p3-r3)^2+(p4-r4)^2 l wd red mat li d On Wed, Sep 9, 2009 at 12:16 PM, James Cross<[email protected]> wrote: > The actual calculation for each element in the vector I am looking to > produce is simply the reference point minus the position. Interesting > that you suggest it might be possible using -reshape-. I am not sure > if I can go down this route as the next step, once I have produced the > vector is to multiply it by its transpose and a diagonal vector of > dimensional saliencies (this is part of the formula for calculating > weighted euclidean distances over multiple dimensions). I have not > used Mata before so I think I better start familiarising myself with > it! > > Thanks, > James > > 2009/9/9 Austin Nichols <[email protected]>: >> James Cross<[email protected]> : >> This would be fairly easy to program in Mata, but you can also >> -reshape- to wide format and calculate the distances using -generate- >> if you know how you are going to treat missing values. Once you can >> specify the actual calculations for your example, it will be easier to >> specify a method. >> >> On Wed, Sep 9, 2009 at 9:12 AM, James Cross<[email protected]> wrote: >>> Hi all, >>> >>> I have a large panel dataset which contains information on different >>> actor positions on different issues (dimensions) within different >>> legislative proposals. Each actor position has a saliency score >>> associated with the position by which I hope to weight the importance >>> of the issue/dimension to that actor. In essence, I am trying to >>> calculate the weighted Euclidean distances between each actors' >>> position and a reference point. >>> >>> In order to do this I first need to create submatrices of the dataset, >>> structured as row vectors, that contain the distances between the two >>> points of interest for each actor for each issue/dimension for each >>> proposal. That is, I should end up with a row vector for each actor of >>> distances between the actors' position and the reference point. The >>> number of elements in this row vector is determined by the number of >>> issues in each proposal in the panel data. While I can do this for >>> each observation individually, I am wondering if it is possible to get >>> stata to do it automatically to save me the effort. >>> >>> The resulting vector will then need to be multiplied by its transpose >>> and a diagonal matrix of issue salience for each actor but that cannot >>> be done until I have created the individual actor distance vectors. >>> There is also an issue with missing data in that sometimes the >>> reference point will be missing and some actors will not have >>> positions on all of the issues/dimensions. >>> >>> The data is structured as follows: >>> >>> >>> proposal issue actor position ref point >>> 04163 1 1 0 0 >>> 04163 2 1 0 0 >>> 04163 1 2 0 0 >>> 04163 2 2 0 0 >>> 00032 1 1 100 0 >>> 00032 2 1 50 n/a >>> 00032 3 1 100 100 >>> 00032 4 1 100 0 >>> 00032 1 2 100 0 >>> 00032 2 2 0 n/a >>> 00032 3 2 0 100 >>> 00032 4 2 0 0 >>> 00032 1 3 40 0 >>> 00032 2 3 100 n/a >>> 00032 3 3 100 100 >>> 00032 4 3 100 0 >>> >>> The resulting vector would look like this for proposal 00032 actor 1: >>> [100 n/a 0 100], and for proposal 04163 actor 1: [0 0]. >>> >>> I am not sure if this is even possible in stata or if it is, how much >>> programming is involved. >>> >>> Any suggestions welcome. >>> Thanks in advance. >>> >>> James * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Weighted Euclidean distances with panel data***From:*James Cross <[email protected]>

**Re: st: Weighted Euclidean distances with panel data***From:*Austin Nichols <[email protected]>

**Re: st: Weighted Euclidean distances with panel data***From:*James Cross <[email protected]>

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