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Bayesian Metric Multidimensional Scaling

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Presentation on theme: "Bayesian Metric Multidimensional Scaling"— Presentation transcript:

1 Bayesian Metric Multidimensional Scaling
Ryan Bakker Keith T. Poole

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13 Algorithm Double-Center the Squared Distances to get starts for the Respondents and Political Figures. Run Nelder-Mead in a Zig-Zag fashion to sharpen the starts. Run L-BFGS Optimization on all the parameters simultaneously using the results of Theorem II. Check the Hessian with numerical and analytical 2nd Derivatives. Use the Configuration from the L-BFGS Optimization as the target Configuration for each element (Configuration in the Slice Sampler) using the results of Theorem II. Run the Slice Sampler 110,000 times with 10,000 Burn-in (random or non-random starts).

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