Posts Tagged ‘ beta ’

Power Analysis and the Probability of Errors

September 22, 2012
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Power Analysis and the Probability of Errors

Power analysis is a very useful tool to estimate the statistical power from a study. It effectively allows a researcher to determine the needed sample size in order to obtained the required statistical power. Clients often ask (and rightfully so) what the sample size should be for a proposed project. Sample sizes end up being

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(nonparametric) Copula density estimation

September 20, 2012
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(nonparametric) Copula density estimation

Today, we will go further on the inference of copula functions. Some codes (and references) can be found on a previous post, on nonparametric estimators of copula densities (among other related things).  Consider (as before) the loss-ALAE data...

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Association and concordance measures

September 12, 2012
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Association and concordance measures

Following the course, in order to define assocation measures (from Kruskal (1958)) or concordance measures (from Scarsini (1984)), define a concordance function as follows: let be a random pair with copula , and with copula . Then define the so-...

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MAT8886 the Dirichlet distribution

February 15, 2012
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MAT8886 the Dirichlet distribution

In the course, still introducing some concept of dependent distributions, we will talk about the Dirichlet distribution (which is a distribution over the simplex of ). Let denote the Gamma distribution with density (on ) Let denote independent...

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MAT8886 exchangeability, credit risk and risk measures

February 10, 2012
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MAT8886 exchangeability, credit risk and risk measures

Exchangeability is an extremely concept, since (most of the time) analytical expressions can be derived. But it can also be used to observe some unexpected behaviors, that we will discuss later on with a more general setting. For instance, in a old...

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Visualizing Bayesian Updating

September 10, 2011
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Visualizing Bayesian Updating

One of the most straightforward examples of how we use Bayes to update our beliefs as we acquire more information can be seen with a simple Bernoulli process. That is, a process which has only two  possible outcomes. Probably the most commonly thought of example is that of a coin toss. The outcome of tossing

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Will I ever be a bayesian statistician ? (part 1)

January 20, 2011
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Will I ever be a bayesian statistician ? (part 1)

Last week, during the workshop on Statistical Methods for Meteorology and Climate Change (here), I discovered how powerful bayesian techniques could be, and that there were more and more bayesian statisticians. So, if I was to fully understand app...

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Design of Experiments – Power Calculations

November 18, 2009
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Prior to conducting an experiment researchers will often undertake power calculations to determine the sample size required in their work to detect a meaningful scientific effect with sufficient power. In R there are functions to calculate either a minimum sample size for a specific power for a test or the power of a test for

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