729 search results for "latex"

Veterinary Epidemiologic Research: Modelling Survival Data – Non-Parametric Analyses

May 23, 2013
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Veterinary Epidemiologic Research: Modelling Survival Data – Non-Parametric Analyses

Next topic from Veterinary Epidemiologic Research: chapter 19, modelling survival data. We start with non-parametric analyses where we make no assumptions about either the distribution of survival times or the functional form of the relationship between a predictor and survival. There are 3 non-parametric methods to describe time-to-event data: actuarial life tables, Kaplan-Meier method, and

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Generating a Markov chain vs. computing the transition matrix

May 23, 2013
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Generating a Markov chain vs. computing the transition matrix

A couple of days ago, we had a quick chat on Karl Broman‘s blog, about snakes and ladders (see http://kbroman.wordpress.com/…) with Karl and Corey (see http://bayesianbiologist.com/….), and the use of Markov Chain. I do believe that this application is truly awesome: the example is understandable by anyone, and computations (almost any kind, from what we’ve tried) are easy to perform....

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Generating a Markov chain vs. computing the transition matrix

May 23, 2013
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Generating a Markov chain vs. computing the transition matrix

A couple of days ago, we had a quick chat on Karl Broman‘s blog, about snakes and ladders (see http://kbroman.wordpress.com/…) with Karl and Corey (see http://bayesianbiologist.com/….), and the use of Markov Chain. I do believe that this application is truly awesome: the example is understandable by anyone, and computations (almost any kind, from what we’ve tried) are easy to perform....

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How Important is Variable Selection?

May 22, 2013
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How Important is Variable Selection?

Very. If you have 10 possible independent regressors, and none of which matter, you have a good chance to find at least one is important. A good chance being 40%: prob(one or more looks important) = 1 – prob(non looks … Continue reading

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Playing cards in Vegas?

May 19, 2013
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Playing cards in Vegas?

In a previous post, a few weeks ago, I mentioned that I will be in Las Vegas by the end of July. And I took the opportunity to write a post on roulette(s). Since some colleagues told me I should take some time to play poker there, I guess I have to understand how to play poker… so I...

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Analyzing a simple experiment with heterogeneous variances using asreml, MCMCglmm and SAS

May 17, 2013
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Analyzing a simple experiment with heterogeneous variances using asreml, MCMCglmm and SAS

I was working with a small experiment which includes families from two Eucalyptus species and thought it would be nice to code a first analysis using alternative approaches. The experiment is a randomized complete block design, with species as fixed … Continue reading

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Forecasting annual totals from monthly data

May 15, 2013
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Forecasting annual totals from monthly data

This question was posed on crossvalidated.com: I have a monthly time series (for 2009–2012 non-stationary, with seasonality). I can use ARIMA (or ETS) to obtain point and interval forecasts for each month of 2013, but I am interested in forecasting the total for the whole year, including prediction intervals. Is there an easy way in R to obtain interval...

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Animations Understood

May 11, 2013
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Animations Understood

When I first saw a graphic made from Yihui’s animation package (Xie, 2012) I was amazed at the magic and thought “I could never do that”. Passage of time… One night I found myself bored and as usual avoiding work. … Continue reading

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AIC & BIC vs. Crossvalidation

May 7, 2013
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AIC & BIC vs. Crossvalidation

Model selection is a process of seeking the model in a set of candidate models that gives the best balance between model fit and complexity (Burnham & Anderson 2002). I have always used AIC for that. But you can also…

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Veterinary Epidemiologic Research: Count and Rate Data – Zero Counts

May 6, 2013
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Veterinary Epidemiologic Research: Count and Rate Data – Zero Counts

Continuing on the examples from the book Veterinary Epidemiologic Research, we look today at modelling count when the count of zeros may be higher or lower than expected from a Poisson or negative binomial distribution. When there’s an excess of zero counts, you can fit either a zero-inflated model or a hurdle model. If zero

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