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Applied and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments.

17 votes
1 answer
10k views

Conjugate prior of the Dirichlet distribution?

What is the conjugate prior distribution of the Dirichlet distribution? Edit: Since I asked this question many years ago, I've written a Python library for working with exponential families. Maximum …
Neil's user avatar
  • 598
3 votes
2 answers
2k views

Why is Beta the maximum entropy distribution over Bernoulli's parameter?

Why is Beta(1,1) the maximum entropy distribution over the bias of a coin expressed as a probability given that: If we express the bias as odds (which is over the support $[0, \infty)$), then Beta-p …
Neil's user avatar
  • 598
3 votes

Peakedness of multimodal distributions

What about information entropy? The smaller it is, the more mass is in peaks.
Neil's user avatar
  • 598
2 votes
Accepted

Estimate gaussian (mixture) density from a set of weighted samples

The usual EM algorithm can be modified for weighted inputs. Following along the Wikipedia presentation, you would use these formulas instead: $a_i = \frac{\sum_{j=1}^N w_j y_{i,j}}{\sum_{j=1}^{N}w_j …
Neil's user avatar
  • 598
2 votes
0 answers
1k views

Estimating Wiener process parameters

Consider a Wiener process with zero drift, infintesimal variance $\sigma^2$, and an unknown starting value $\nu$. That is, \begin{align} Y_t \sim \mathcal{N}(\nu, t\sigma^2). \end{align} Now, su …
Neil's user avatar
  • 598
1 vote

statistical approach to multinomial distribution

The conjugate prior of the multinomial distribution is Dirichlet -- it is a distribution over the parameters (the probabilities of outcomes) of the multinomial. Define D = Dirichlet(X + 1) (the 1 …
Neil's user avatar
  • 598
0 votes

What is the probabilistic counterpart of weighted K-Means

Are you looking for a GMM with weighted samples? Please see my answer
Neil's user avatar
  • 598