Difference between revisions of "Eleisha's Segment 27: Mixture Models"

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(Created page with "<b> To Calculate: </b> The file Media:Mixturevals.txt contains 1000 values, each drawn either with probability c from the distribution <math>\text{Exponential}(\beta) <...")
 
 
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1. In problem 3, above, you assumed some definite prior for <math>c</math> . What if <math> c </math> is itself drawn (just once for the whole data set) from a distribution <math> \text{Beta}(\mu,\nu) </math>, with unknown hyperparameters <math> \mu,\nu </math> . How would you now estimate the Bayes posterior distribution of <math> \beta </math> , marginalizing over everything else?
 
1. In problem 3, above, you assumed some definite prior for <math>c</math> . What if <math> c </math> is itself drawn (just once for the whole data set) from a distribution <math> \text{Beta}(\mu,\nu) </math>, with unknown hyperparameters <math> \mu,\nu </math> . How would you now estimate the Bayes posterior distribution of <math> \beta </math> , marginalizing over everything else?
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<b> Back To: </b> [[Eleisha Jackson]]

Latest revision as of 11:51, 3 April 2014

To Calculate:

The file Media:Mixturevals.txt contains 1000 values, each drawn either with probability c from the distribution Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \text{Exponential}(\beta) } (for some constant Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \beta } ), or otherwise (with probability Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 1-c } ) from the distribution Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle p(x) = (2/\pi)/(1+x^2),\; x>0 } .

1. Write down an expression for the probability of the file's data given some values for the parameters Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \beta } and Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle c } .

2. Calculate numerically the maximum likelihood values of Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \beta } and Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle c } .

3. Estimate numerically the Bayes posterior distribution of Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \beta } , marginalizing over c as a nuisance parameter. (You'll of course have to make some assumption about priors.)

To Think About:

1. In problem 3, above, you assumed some definite prior for Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle c} . What if Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle c } is itself drawn (just once for the whole data set) from a distribution Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \text{Beta}(\mu,\nu) } , with unknown hyperparameters Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \mu,\nu } . How would you now estimate the Bayes posterior distribution of Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \beta } , marginalizing over everything else?

Back To: Eleisha Jackson