A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general
spatially-or temporally-dependent data, imposing the belief that proximate data are more …

… Here, we leverage a logistic stick-breaking representation and recent innovations in
Pólya-gamma augmentation to reformulate the multinomial distribution in terms of latent variables …

We propose a class of kernel stick-breaking processes for uncountable collections of dependent
random probability measures. The process is constructed by first introducing an infinite …

… stick-breaking likelihood function for categorical LGMs that exploits accurate linear and quadratic
bounds on the logistic log-… inference in multinomial Gaussian process classification and …

… stick-breaking construction via a continuation–ratio logistic regression, within an exponential
family representation. We study the theoretical properties, and leverage this result to derive …

… review multinomial logistic regression (MLR). We then use the stick-breaking construction
to … to transform binary logistic regression under stick breaking into multinomial regression. In …

… In the general form of the stick-breaking construction (… intuition, we introduce the following
stick-breaking process: … We now establish that the Bernoulli stick-breaking process mixture …

Stick-breaking (SB) processes are often adopted in Bayesian mixture models for generating
mixing weights. When covariates influence the sizes of clusters, SB mixtures are particularly …

… of the stick-breaking processes … process from the kernel stick-breaking processes (Reich
and Fuentes Citation2007; Fuentes and Reich Citation2013), the probit stick-breaking process (…

… The ‘Markovian stick-breaking’ process is then represented … ] that such Markovian stick-breaking
processes connect to the … of the Markovian stick-breaking process in Theorem 4. Then, …