Articles

type: Journal
Title DOI Date
Population food intake clusters and cardiovascular disease incidence: a Bayesian quantifying of a prospective population-based cohort study in a low and middle-income country 10.3389/fnut.2023.1150481
Dry sliding wear characteristics of NiP/TiN duplex coated aluminum alloy and wear analysis using RSM #
A novel approach for evaluation of load bearing capacity of duplex coatings on aluminum alloy using PLS and SVR models. #
Regularization in Dynamic Random Intercepts Models for Analysis of Longitudinal Data 10.1111/sjos.12592
Spike Sorting of Non-Stationary Data in Successive Intervals Based on Dirichlet Process Mixtures #
Detection of alteration zones using the Dirichlet process Stick-Breaking model-based clustering algorithm to hyperion data: the case study of Kuh-Panj porphyry copper deposits, Southern Iran 10.1080/10106049.2022.2025917
Application of Dirichlet Process and Support Vector Machine Techniques for Mapping Alteration Zones Associated with Porphyry Copper Deposit Using ASTER Remote Sensing Imagery 10.3390/min11111235
Risk factors associated with intensive care unit (ICU) admission and in-hospital death among adults hospitalized with COVID-19: a two-center retrospective observational study in tertiary care hospitals 10.1007/s10140-021-01903-8
Longitudinal Modeling of Non-pharmacological factors Related to Frequency, Severity and Duration in both Migraine and Tension Type Headaches #
A population-based cohort study on the association of dietary patterns with sleep duration: A Joint modeling by mental health status 10.21203/rs.3.rs-37401/v1
Efficient Bayesian approach to saliency detection based on Dirichlet process mixture 10.1049/iet-ipr.2017.0267
An application of Dirichlet process in clustering subjects via variance shift models A course-evaluation study #
A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension 10.1080/00949655.2016.1196689
The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture 10.1007/s11634-016-0262-x
type: Conference
Title Date
The Initial Conditions Problem in L1 Regularization of Dynamic Random-Intercepts Models
Endogeneity problem in recurrent event data analysis
Spike sorting Which clustering method should be chosen Which circumstances affect this selection
Clustering individuals with longitudinal observations based on their distributional behavior via Dirichlet processes
A Bayesian semi-parametric approach to clustering longitudinal count data with missing values
A semi-parametric model-based clustering of subjects with longitudinal observations