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A study on bathroom water-uses demand prediction model using Weibull regression
Journal of the Korean Data & Information Science Society 2018;29:929-36
Published online July 31, 2018
© 2018 Korean Data and Information Science Society.

Jinnam Jo1

1Department of Information and Statistics, Dongduk Women’s University
Correspondence to: Professor, Department of Statistics and Information, Dongduk Women’s University, Seoul, 02748, Korea. E-mail: jinnam@dongduk.ac.kr
Received June 29, 2018; Revised July 14, 2018; Accepted July 16, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This study develops a predictive model for bathroom water end-uses based on the data that have measured household characteristics, housing characteristics and other items, surveyed over 3 years in Korea. However, the measured data were left-skewed and it were not fitted to normal distribution. The parameter estimates were biased when using a multiple regression model. In addition, the results of the testing for the model were usually of significance due to the tiny residual from a large number of observations. In order to solve the problem, we suggested log-normal regression model and Weibull regression model as alternative. The results of this research can be utilized at the planning stages of water and waste water facilities.
Keywords : Bathroom water-uses, log-normal regression model, prediction model, water use pattern, Weibull regression model.