A latent variable approach to impute missing values: with application in air pollution data.

• Other Authors: Lee, Wing-Yeong.
• Format: Others
• Language: English; Chinese
• Published: 1999
• Subjects: Latent structure analysis; Latent variables; Air > Pollution > Mathematical models
• Online Access: http://library.cuhk.edu.hk/record=b5890038; http://repository.lib.cuhk.edu.hk/en/item/cuhk-322728

Wing-Yeong Lee. === Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. === Includes bibliographical references (leaves 73-75). === Abstracts in English and Chinese. === Chapter Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Introduction --- p.1 === Chapter 1.2 --- The observed data --- p.3 === Chapter 1.3 --- Outline of the thesis --- p.8 === Chapter Chapter 2 --- Modeling using Latent Variable --- p.9 === Chapter Chapter 3 --- Imputation Procedure --- p.16 === Chapter 3.1 --- Introduction --- p.16 === Chapter 3.2 --- Introduction to Metropolis-Hastings algorithm --- p.18 === Chapter 3.3 --- Introduction to Gibbs sampler --- p.19 === Chapter 3.4 --- Imputation step --- p.21 === Chapter 3.5 --- Initialization of the missing values by regression --- p.23 === Chapter 3.6 --- Initialization of the parameters and creating the latent variable and noises --- p.27 === Chapter 3.7 --- Simulation of Y's --- p.30 === Chapter 3.8 --- Simulation of the parameters --- p.34 === Chapter 3.9 --- Simulation of T by use of the Metropolis-Hastings algorithm --- p.41 === Chapter 3.10 --- Distribution of Vij's given all other values --- p.44 === Chapter 3.11 --- Simulation procedure of Vij's --- p.46 === Chapter Chapter 4 --- Data Analysis of the Pollutant Data --- p.48 === Chapter 4.1 --- Convergence of the process --- p.48 === Chapter 4.2 --- Data analysis --- p.53 === Chapter Chapter 5 --- Conclusion --- p.69 === REFERENCES --- p.73