Search
Search Results
-
Dynamic hierarchical Dirichlet processes topic model using the power prior approach
The hierarchical Dirichlet processes (HDP) topic model is a Bayesian nonparametric model that provides a flexible mixed-membership to documents...
-
A Unified Approach to Hierarchical Random Measures
Hierarchical models enjoy great popularity due to their ability to handle heterogeneous groups of observations by leveraging on their underlying...
-
A Note on the Dependence Structure of Hierarchical Completely Random Measures
Hierarchical models offer a principled framework to make inference and predictions on different (groups of) observations by leveraging their common...
-
Bayesian modeling via discrete nonparametric priors
The availability of complex-structured data has sparked new research directions in statistics and machine learning. Bayesian nonparametrics is at the...
-
Penalized Latent Dirichlet Allocation Model in Single-Cell RNA Sequencing
Single-cell RNA sequencing (scRNA-seq) quantifies RNA transcripts at individual cell level, providing cellular-level resolution of gene expression...
-
Exchangeable min-id sequences: Characterization, exponent measures and non-decreasing id-processes
We establish a one-to-one correspondence between (i) exchangeable sequences of random variables whose finite-dimensional distributions are minimum...
-
A Partition Dirichlet Process Model for Functional Data Analysis
Recently, extensions of the Dirichlet process to the functional domain have been presented in the literature. These processes can be classified based...
-
Empirical estimates for heteroscedastic hierarchical dynamic normal models
The available heteroscedastic hierarchical models perform well for a wide range of real-world data, but for data sets that exhibit a dynamic...
-
A general guide in Bayesian and robust Bayesian estimation using Dirichlet processes
In this paper, we investigate Bayesian and robust Bayesian estimation of a wide range of parameters of interest in the context of Bayesian...
-
Semi-parametric survival analysis via Dirichlet process mixtures of the First Hitting Time model
Time-to-event data often violate the proportional hazards assumption inherent in the popular Cox regression model. Such violations are especially...
-
Enhancing social media post popularity prediction with visual content
Our study presents a framework for predicting image-based social media content popularity that focuses on addressing complex image information and a...
-
Sampling hierarchies of discrete random structures
Hierarchical normalized discrete random measures identify a general class of priors that is suited to flexibly learn how the distribution of a...
-
Bayesian modeling of the Mnemonic Similarity Task using multinomial processing trees
The Mnemonic Similarity Task (MST, Stark et al. in Neuropsychologia 51:2442–2449.
https://doi.org/10.1016/j.neuropsychologia.2012.12.014 ...
-
Bayesian Latent Gaussian Models
Bayesian latent Gaussian models are Bayesian hierarchical models that assign Gaussian prior densities to the latent parameters. In this chapter, we...
-
On Properties and Applications of Gaussian Subordinated Lévy Fields
We consider Gaussian subordinated Lévy fields (GSLFs) that arise by subordinating Lévy processes with positive transformations of Gaussian random...
-
Identification of Key Concerns and Sentiments Towards Data Quality and Data Strategy Challenges Using Sentiment Analysis and Topic Modeling
In the era of Fourth Industrial Revolution, data and information became a valuable resource. In this data-driven economy, it is extremely important...
-
Clustering and Latent Factor Models
Hierarchical modelsHierarchical model were previously discussed in Sect. 3.3 . This chapter gives further details...
-
Bayesian Ideas in Survey Sampling: The Legacy of Basu
Survey sampling and, more generally, Official Statistics are experiencing an important renovation time. On one hand, there is the need to exploit the...
-
Statistical Challenges in Mutational Signature Analyses of Cancer Sequencing Data
Cancer is a disease driven and characterised by mutations in the DNA. Different categorisations of DNA mutations have allowed the identification of...
-
A Statistical Perspective on the Challenges in Molecular Microbial Biology
High throughput sequencing (HTS)-based technology enables identifying and quantifying non-culturable microbial organisms in all environments....
