Title
Bayesian Analysis of Binary Sales Data for Several Industries
Faculty Advisor or Committee Member
Balgobin Nandram, Advisor
Identifier
etd-043015-140244
Abstract
The analysis of big data is now very popular. Big data may be very important for companies, societies or even human beings if we can take full advantage of them. Data scientists defined big data with four Vs: volume, velocity, variety and veracity. In a short, the data have large volume, grow with high velocity, represent with numerous varieties and must have high quality. Here we analyze data from many sources (varieties). In small area estimation, the term ``big data' refers to numerous areas. We want to analyze binary for a large number of small areas. Then standard Markov Chain Monte Carlo methods (MCMC) methods do not work because the time to do the computation is prohibitive. To solve this problem, we use numerical approximations. We set up four methods which are MCMC, method based on Beta-Binomial model, Integrated Nested Normal Approximation Model (INNA) and Empirical Logistic Transform (ELT) method. We compare the processing time and accuracies of these four methods in order to find the fastest and reasonable accurate one. Last but not the least, we combined the empirical logistic transform method, the fastest and accurate method, with time series to explore the sales data over time.
Publisher
Worcester Polytechnic Institute
Degree Name
MS
Department
Mathematical Sciences
Project Type
Thesis
Date Accepted
2015-04-30
Copyright Statement
All authors have granted to WPI a nonexclusive royalty-free license to distribute copies of the work. Copyright is held by the author or authors, with all rights reserved, unless otherwise noted. If you have any questions, please contact wpi-etd@wpi.edu.
Accessibility
Unrestricted
Repository Citation
Chen, Zhilin, "Bayesian Analysis of Binary Sales Data for Several Industries" (2015). Masters Theses (All Theses, All Years). 596.
https://digitalcommons.wpi.edu/etd-theses/596
Subjects
inna, empirical logistic transform, beta-binomial, big data, time-series, mcmc