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Dennis's blog 2.0

Dennis's blog 2.0. June 2, 2014. I’ve just arxived. A paper on “lazy ABC”. This post is a quick non-technical overview of the contents. From the prior density. From the model conditional on. Return to step 1 if fewer than N simulations have been performed. Step 3 accepts if the simulated data. Is sufficiently close to the observed data. Based on a distance function. The accepted parameter values. Can then be used for inference. In particular the posterior expectation of some function. Could be the first ...

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Dennis's blog 2.0. June 2, 2014. I’ve just arxived. A paper on “lazy ABC”. This post is a quick non-technical overview of the contents. From the prior density. From the model conditional on. Return to step 1 if fewer than N simulations have been performed. Step 3 accepts if the simulated data. Is sufficiently close to the observed data. Based on a distance function. The accepted parameter values. Can then be used for inference. In particular the posterior expectation of some function. Could be the first ...

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Dennis's blog 2.0 | dennisprangleblog.wordpress.com Reviews

https://dennisprangleblog.wordpress.com

Dennis's blog 2.0. June 2, 2014. I’ve just arxived. A paper on “lazy ABC”. This post is a quick non-technical overview of the contents. From the prior density. From the model conditional on. Return to step 1 if fewer than N simulations have been performed. Step 3 accepts if the simulated data. Is sufficiently close to the observed data. Based on a distance function. The accepted parameter values. Can then be used for inference. In particular the posterior expectation of some function. Could be the first ...

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dennisprangleblog.wordpress.com

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Lazy ABC | Dennis's blog 2.0

https://dennisprangleblog.wordpress.com/2014/06/02/lazy-abc

Dennis's blog 2.0. I’ve just arxived. A paper on “lazy ABC”. This post is a quick non-technical overview of the contents. From the prior density. From the model conditional on. Return to step 1 if fewer than N simulations have been performed. Step 3 accepts if the simulated data. Is sufficiently close to the observed data. Based on a distance function. The accepted parameter values. Can then be used for inference. In particular the posterior expectation of some function. Has the Monte Carlo estimate.

2

July | 2011 | Dennis's blog 2.0

https://dennisprangleblog.wordpress.com/2011/07

Dennis's blog 2.0. July 12, 2011. I’ve started tidying up some code from my thesis to create an R package called “gk”. Containing functions for the g-and-k distribution. This defined by its quantile function (i.e. its inverse cdf). Is the standard normal cdf and. To explain, if u is a random variable with a uniform distribution on [0,1], then. Follows a standard normal distribution and Q(z) follows the g-and-k distribution. Indeed this is a straightforward method (the inversion method) for simulation.

3

December | 2011 | Dennis's blog 2.0

https://dennisprangleblog.wordpress.com/2011/12

Dennis's blog 2.0. Semi-automatic ABC: ordinary meeting. December 19, 2011. Last week I had the pleasure of taking part in an RSS ordinary meeting. On my paper with Paul Fearnhead. And I thought I’d take the chance to write up my notes on it. They were a bit hurried so apologies if I misrepresent what anyone said! That ABC is exact given measurement (or model) error. Then I gave a (hopefully) accessible introductory talk on the paper, the slides of which are here. He also questioned whether our asymptoti...

4

Semi-automatic ABC – list of typos | Dennis's blog 2.0

https://dennisprangleblog.wordpress.com/2011/12/08/semi-automatic-abc-list-of-typos

Dennis's blog 2.0. Semi-automatic ABC – list of typos. I’m very pleased that next week my paper with Paul Fearnhead is being discussed. At the Royal Statistical Society. Unfortunately there are still several typos in the manuscript. So I’ll keep an up to date list of them here. This is expanded from a comment. I wrote on Xian Robert’s blog – thanks to him and others for spotting these. I’ll post up a link to my summary slides on the paper for the pre-ordinary meeting. In several places where. Thanks, I&#...

5

gk R package | Dennis's blog 2.0

https://dennisprangleblog.wordpress.com/2011/07/12/gk-r-package

Dennis's blog 2.0. I’ve started tidying up some code from my thesis to create an R package called “gk”. Containing functions for the g-and-k distribution. This defined by its quantile function (i.e. its inverse cdf). Is the standard normal cdf and. To explain, if u is a random variable with a uniform distribution on [0,1], then. Follows a standard normal distribution and Q(z) follows the g-and-k distribution. Indeed this is a straightforward method (the inversion method) for simulation. A few technical n...

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Blog 2.0 | Dennis's Computational Stats PhD Blog

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Dennis's Computational Stats PhD Blog. A record of what I've learnt along the way. July 12, 2011. As I’m no longer a PhD student (assuming my viva next week isn’t a disaster! I’m shifting to a new blog. Without “phd” in the title for occasional research related posts in future. Laquo; A practical use for - in R. Leave a Reply Cancel reply. Enter your comment here. Fill in your details below or click an icon to log in:. Address never made public). You are commenting using your Google account. ( Log Out.

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Dennis's blog 2.0

Dennis's blog 2.0. June 2, 2014. I’ve just arxived. A paper on “lazy ABC”. This post is a quick non-technical overview of the contents. From the prior density. From the model conditional on. Return to step 1 if fewer than N simulations have been performed. Step 3 accepts if the simulated data. Is sufficiently close to the observed data. Based on a distance function. The accepted parameter values. Can then be used for inference. In particular the posterior expectation of some function. Could be the first ...

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