edu.mit.util.stats
Class Stats
java.lang.Object
edu.mit.util.stats.Stats
public class Stats
- extends Object
Constructor Summary |
Stats()
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Method Summary |
static double |
computeDispersionGradient(int len,
double mean_len,
double log_dispersion,
FastDigamma digamma)
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static double[] |
computeLogMultinomial(double[] counts,
double prior)
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static double[] |
computeMultinomial(double[] counts,
double prior)
computeMultinomial
builds the expected multinomial given counts and a symmetric dirichlet
theta = argmax_theta p(theta | counts, prior)
= argmax_theta p(counts | theta) p(theta | prior)
this is in closed form due to conjugacy |
static
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generateOrderings(List<T> stuff)
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static double |
kldiv(double[] distrib1,
double[] distrib2)
Computes the KL divergence of the distribution. |
static double |
logProbLogMultinomial(double[] x,
double[] loga)
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static double |
logProbMultinomial(double[] x,
double[] a)
computes the log-probability of a bag-of-words observation x, given
the multinomial probability distribution a |
static void |
main(String[] argv)
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static double |
myLogGammaPdf(double x,
double mean,
double variance)
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static double |
myLogNBinPdf(int k,
double r,
double p)
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static double |
myLogNBinPdf2(int z,
double m,
double k)
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Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
MAX_LOG_DISPERSION
public static double MAX_LOG_DISPERSION
Stats
public Stats()
kldiv
public static double kldiv(double[] distrib1,
double[] distrib2)
- Computes the KL divergence of the distribution. Actually
it's the skewed divergence, from Lee 2001
generateOrderings
public static <T> List<List<T>> generateOrderings(List<T> stuff)
myLogNBinPdf
public static double myLogNBinPdf(int k,
double r,
double p)
myLogNBinPdf2
public static double myLogNBinPdf2(int z,
double m,
double k)
myLogGammaPdf
public static double myLogGammaPdf(double x,
double mean,
double variance)
computeMultinomial
public static double[] computeMultinomial(double[] counts,
double prior)
- computeMultinomial
builds the expected multinomial given counts and a symmetric dirichlet
theta = argmax_theta p(theta | counts, prior)
= argmax_theta p(counts | theta) p(theta | prior)
this is in closed form due to conjugacy
computeLogMultinomial
public static double[] computeLogMultinomial(double[] counts,
double prior)
logProbMultinomial
public static double logProbMultinomial(double[] x,
double[] a)
- computes the log-probability of a bag-of-words observation x, given
the multinomial probability distribution a
logProbLogMultinomial
public static double logProbLogMultinomial(double[] x,
double[] loga)
computeDispersionGradient
public static double computeDispersionGradient(int len,
double mean_len,
double log_dispersion,
FastDigamma digamma)
main
public static void main(String[] argv)
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