Can someone explain how the mean and standard deviation are defined for normpdf from the following matlab example?
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I m looking at the following example, http://fr.mathworks.com/help/stats/examples/bayesian-analysis-for-a-logistic-regression-model.html
The code
prior1 = @(b1) normpdf(b1,0,20); % prior for intercept
prior2 = @(b2) normpdf(b2,0,20);
The mean is defined as 0 and the standard deviation is defined as 20. I know for a standard normal distribution the mean is defined as 0 and the standard deviation is 1. However it isn't explained how these the inputs 0 and 20 are obtained which is frustrating.
4 Comments
Adam
on 8 Dec 2015
They are specific to that pdf, as you can see in the graph shown in that example. You can see the 20 standard deviation coming through in the halfwidth of the pdf. If you put 50 in then your half width would be around 50.
Answers (1)
the cyclist
on 8 Dec 2015
Ronan, I think that example assumes a certain amount of knowledge of Bayesian analysis. Maybe you have some of that knowledge, and maybe you don't.
The values you ask about parameterize the prior probability distribution. In this example, these values indicate that the analyst had evidence (maybe a prior experiment or literature) that the distribution with mean 0 and standard deviation of 20. They are a bit "out of the blue" here, but in a real application they would not be arbitrary. They would be driven by prior knowledge.
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