Re: [eigen] cache-friendly matrix inverse |

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*To*: eigen@xxxxxxxxxxxxxxxxxxx*Subject*: Re: [eigen] cache-friendly matrix inverse*From*: Robert Lupton the Good <rhl@xxxxxxxxxxxxxxxxxxx>*Date*: Wed, 13 May 2009 11:09:26 -0700

I'm not sure that this is still on-topic, but if you have a model theta = M y + epsilon (theta, y, and epsilon are vectors; M is a non-square matrix) where <epsilon epsilon^T> = V then the least-squares estimate for theta is theta = (M^T V^{-1} M)^{-1} M V^{-1} y with covariance (M^T V^{-1} M)^{-1} So you really need to invert a matrix. You can invert it any way you like (e.g. eigen-value decomposition; Gaussian elimination; ...) but invert it you must. R

**Follow-Ups**:**Re: [eigen] cache-friendly matrix inverse***From:*Christian Mayer

**References**:**[eigen] cache-friendly matrix inverse***From:*Benoit Jacob

**Re: [eigen] cache-friendly matrix inverse***From:*Christian Mayer

**Re: [eigen] cache-friendly matrix inverse***From:*Robert Lupton the Good

**Re: [eigen] cache-friendly matrix inverse***From:*Christian Mayer

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