# Monthly Archives: August 2007

## GGobi 2.1.6

August 20, 2007
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Just a quick note to let you know that GGobi 2.1.6 has been releasedand is available from Windows, Mac (with easy installer) and Linuxfrom http://www.ggobi.org/downloads. The changes are largely internalwith a few more bugs being fixed.We are working ...

## GGobi 2.1.6

August 20, 2007
By

Just a quick note to let you know that GGobi 2.1.6 has been releasedand is available from Windows, Mac (with easy installer) and Linuxfrom http://www.ggobi.org/downloads. The changes are largely internalwith a few more bugs being fixed.We are working ...

## GillespieSSA 0.1-0 is released

August 19, 2007
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I just submitted the first release of the GillespieSSA package to CRAN. After much debating I finally decided to adhere to the unwritten R version numbering policy of starting really really low (and asymptotically approaching 1.0-0) . Thus, the first … Continue reading →

## Offset in glm ()

August 17, 2007
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To add an offset to the linear predictor of a generalized linear model (or models from the survival package such as coxph and clogit), use offset(x) in the formula. This will add an offset to the linear predictor with known coefficient 1.

## Offset in glm ()

August 17, 2007
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To add an offset to the linear predictor of a generalized linear model (or models from the survival package such as coxph and clogit), use offset(x) in the formula. This will add an offset to the linear predictor with known coefficient 1.

August 16, 2007
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## Review of Jim Albert’s Bayesian Computation with R

August 14, 2007
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When I first read Andrew Gelman's quick off-the-cuff review of the book Bayesian Computation with R, I thought it was a bit harsh. So did Gelman.I thumbed through the book at the joint statistical meetings, and decided to buy it along with Bayesian Cor...

## A new default prior distribution for logistic and other regression coefficients

August 14, 2007
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This (by Aleks, Grazia, Yu-Sung, and myself) is really cool. Here's the abstract: We propose a new prior distribution for classical (non-hierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mea...