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Federal Cuts and Public Health: Social Media Sentiment Among Federal Employees. [PDF]

J Med Internet Res
Wang Y, Crenshaw AN, Reis R.
europepmc   +1 more source

Common TF-IDF variants arise as key components in the test statistic of a penalized likelihood-ratio test for word burstiness. [PDF]

Discov Comput
Ahmed Z, Sheridan P, McIsaac M, Farooque AA.   +3 more
europepmc   +1 more source

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A bivariate Dirichlet process

Statistics and Probability Letters, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stephen Walker, Pietro Muliere
exaly   +3 more sources

Conjugacy as a Distinctive Feature of the Dirichlet Process

Scandinavian Journal of Statistics, 2006
The authors introduce a class of normalized homogeneous random measures with independent increments (normal HRMI). These measures are obtained by normalization of time-dependent subordinators. Formulas for the variance-covariance structure and the skewness of such measures are derived.
Antonio Lijoi
exaly   +3 more sources

The Nested Dirichlet Process

Journal of the American Statistical Association, 2008
In multicenter studies, subjects in different centers may have different outcome distributions. This article is motivated by the problem of nonparametric modeling of these distributions, borrowing information across centers while also allowing centers to be clustered.
Abel Rodríguez, Alan Gelfand
exaly   +3 more sources

Functional dirichlet process

Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013
Dirichlet process mixture (DPM) model is one of the most important Bayesian nonparametric models owing to its efficiency of inference and flexibility for various applications. A fundamental assumption made by DPM model is that all data items are generated from a single, shared DP.
Lijing Qin, Xiaoyan Zhu 0001
openaire   +1 more source

Dependent mixtures of Dirichlet processes

Computational Statistics & Data Analysis, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Spyridon J. Hatjispyros, Theodoros Nicoleris, Stephen G. Walker   +2 more
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On Non-Continuous Dirichlet Processes

Journal of Theoretical Probability, 2003
A Dirichlet process is an adapted càdlàg process that can be represented as the sum of a semimartingale and an adapted continuous process with zero quadratic variation. For continuous Dirichlet processes, a pathwise Itô calculus was introduced by \textit{H. Föllmer} [in: Séminaire de probabilités XV. Lect. Notes Math. 850, 143-150 (1981; Zbl 0461.60074)
Coquet, François, Mémin, Jean, Slominski, Leszek   +2 more
openaire   +4 more sources

Robust Dirichlet Process mixtures

2011 Seventh International Conference on Natural Computation, 2011
Non-parametric Dirichlet Process mixture (DPM) approaches for density estimation and clustering allow for automatic model selection. In this paper, we aim to develop robust DPM algorithm for clustering datasets with scatter objects, or outliers. In the developed mean-field variational inference algorithms, the auxiliary posterior distributions are ...
Jianyong Sun, Jonathan M. Garibaldi
openaire   +1 more source

Models with products of Dirichlet processes

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
Nonparametric Bayesian models are often preferred over parametric models due to their superior flexibility in interpreting data. A strong motivation for the use of these models is the desire of avoiding the assumptions that are necessary for parametric models.
Petar M. Djuric, André Ferrari
openaire   +2 more sources