dirichletprocess

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I noticed that in the latest release the `LikelihoodDP()` function resizes the `likelihoodValues` object using the code `dim(likelihoodValues)

sergioventurini

Hello, I'm struggling with the code for the Predictive.mvnormal() function. In particular, I was wondering why in the last if() statement that computes the gamma_contrib scalar you used twice 'prod(vapply(seq_along(d)...

sergioventurini

Hi there, I have another question regarding the size of the 'theta' parameters in the Likelihood.normal() function: it appears that the object returned by that function is a vector, while...

sergioventurini

I am a little confused about the role of "n" in the PosteriorDrawer.exp function. If n shows sample size, why should n be equal to 1? If n shows the...

Kharrati-Kopaei

Different number of clusters of two converged dp model objects trained on same dataset?

3

Hi @dm13450, I was using the dirichletprocess package twice on the same data set, I called the two objects dp, and dp2 (see below). I checked convergence following your approach...

wseis

clustering high-dimensional data?

6

Hi @dm13450 I am trying to get dirichletprocess working for clustering a high-dimensional data set. For example https://web.stanford.edu/~hastie/ElemStatLearn/datasets/zip.train.gz has 256 features. Using dirichletprocess::DirichletProcessMvnormal would result in a 256 x 256...

tdhock

add new fit_continue

1

filippofiocchi

constrain clusters to have common parameters?

1

hi @dm13450 first of all thanks for the great JSS article / vignette about dirichletprocess, which is super helpful. I am using it for teaching a CS class about unsupervised...

tdhock

prior choice for beta2

4

Hi, I am trying to apply to real data the function dirichletprocess beta but I got an extrange result. My goal is to cluster a one dimensional vector of percentages...

csetraynor

Indian buffets

1

Hello, first of all thanks for this great package. I wonder if there are any plans to implement IBPs as well or if this already somewhere supported? Cheers, Simon

dirmeier