1005 search results for "Latex"

Riemann, Langevin & Hamilton [reply]

September 27, 2010
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Riemann, Langevin & Hamilton [reply]

Here is a (prompt!) reply from Mark Girolami corresponding to the earlier post: In preparation for the Read Paper session next month at the RSS, our research group at CREST has collectively read the Girolami and Calderhead paper on Riemann manifold Langevin and Hamiltonian Monte Carlo methods and I hope we will again produce a

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Effective sample size

September 23, 2010
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Effective sample size

In the previous days I have received several emails asking for clarification of the effective sample size derivation in “Introducing Monte Carlo Methods with R” (Section 4.4, pp. 98-100). Formula (4.3) gives the Monte Carlo estimate of the variance of a self-normalised importance sampling estimator (note the change from the original version in Introducing Monte

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A (fast!) null model of bipartite networks

September 12, 2010
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A (fast!) null model of bipartite networks

One of the challenges for ecologists working with trophic/interaction networks is to understand their organization. One of the possible approaches is to compare them across a random model, with more or less constraints, in order to estimate the departure from randomness. To this effect, null models have been developed. The basic idea behind a null

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Typo in Chapter 5

September 9, 2010
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Typo in Chapter 5

Gilles Guillot from Technical University of Denmark taught a course based on our R book and he pointed out to me several typos in Chapter 5 of “Introducing Monte Carlo Methods with R”: p.137 second equation from bottom should be p. 138  Example 5.7 denominator in the gradient should be

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Random dive MH

September 1, 2010
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Random dive MH

A new Metropolis-Hastings algorithm that I would call “universal” was posted by Somak Dutta yesterday on arXiv. Multiplicative random walk Metropolis-Hastings on the real line contains a different Metropolis-Hastings algorithm called the random dive. The proposed new value x’ given the current value x is defined by when is a random variable on . Thus,

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Hyper-g priors

August 30, 2010
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Hyper-g priors

Earlier this month, Daniel Sabanés Bové and Leo Held posted a paper about g-priors on arXiv. While I glanced at it for a few minutes, I did not have the chance to get a proper look at it till last Sunday. The g-prior was first introduced by the late Arnold Zellner for (standard) linear models,

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ProjectTemplate

August 26, 2010
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Introduction As many people already know, I’ve recently uploaded a new R package called ProjectTemplate to GitHub and CRAN. The ProjectTemplate package provides a function, create.project(), that automatically builds a directory for a new R project with a clean sub-directory structure and automatic data and library loading tools. My hope is that standardized data loading,

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In Search of Power-laws: WikiLeaks Edition

August 26, 2010
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In Search of Power-laws: WikiLeaks Edition

Yesterday, a commenter reminded me of the very popular hobby among scientists of searching for power-law distributions in large event data. While the commonality of scale invariance in event data is quite well known—particularly with respect to conflict data—this has not prevented many researchers from seeking and finding these patterns in data. As the commenter notes,

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Global Temperature Proxy Reconstructions ~ now with CO2 forcing

August 26, 2010
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Global Temperature Proxy Reconstructions ~ now with CO2 forcing

Previously, I did a simple Bayesian projection of recent temperature using proxy data and the methods shown in McShane and Wyner (2010). I showed that when you take out the last 30 years of data (1969~1998), the projection does not track the recent uptick in temperatures well. The “projection” is a simple unparametric bootstrap which

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Demonstration of {estout}

August 24, 2010
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Demonstration of {estout}

I wrote a short talk demonstrating the use the R package {estout} for tonight’s New England R Users Group meeting.  NB this is not a discussion of the econometric model, but rather a demonstration of how to get publication-quality results out of R efficiently. The basic functions of {estout} are modeled on the Stata package estout.

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