23 citations · 44 across the 10 of their papers we have counts for
10 papers
Particle swarm optimization with Applications to Maximum Likelihood Estimation and Penalized Negative Binomial Regression
Sisi Shao, Junhyung Park, Weng Kee Wong
General purpose optimization routines such as nlminb, optim (R) or nlmixed (SAS) are frequently used to estimate model parameters in nonstandard distributions. This paper presents…
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic
Zhe Fei, Yevgen Ryeznik, Oleksandr Sverdlov +2
In the era of big data, standard analysis tools may be inadequate for making inference and there is a growing need for more efficient and innovative ways to collect, process, analy…
Orthogonal Subsampling for Big Data Linear Regression
Lin Wang, Jake Elmstedt, Weng Kee Wong +1
The dramatic growth of big datasets presents a new challenge to data storage and analysis. Data reduction, or subsampling, that extracts useful information from datasets is a cruci…
Exploration Enhancement of Nature-Inspired Swarm-based Optimization Algorithms
Kwok Pui Choi, Enzio Hai Hong Kam, Tze Leung Lai +2
Nature-inspired swarm-based algorithms have been widely applied to tackle high-dimensional and complex optimization problems across many disciplines. They are general purpose optim…
Statistical Analysis of Complex Computer Models in Astronomy
Joshua Lukemire, Qian Xiao, Abhyuday Mandal +1
We introduce statistical techniques required to handle complex computer models with potential applications to astronomy. Computer experiments play a critical role in almost all fie…
T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method
Yuguang Yue, Lieven Vandenberghe, Weng Kee Wong
We consider T-optimal experiment design problems for discriminating multi-factor polynomial regression models where the design space is defined by polynomial inequalities and the r…