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Process monitoring using inflated beta regression control chart
- Source :
- PLoS ONE, Vol 15, Iss 7, p e0236756 (2020), PLoS ONE
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- This paper provides a general framework for controlling quality characteristics related to control variables and limited to the intervals (0, 1], [0, 1), or [0, 1]. The proposed control chart is based on the inflated beta regression model considering a reparametrization of the inflated beta distribution indexed by the response mean, which is useful for modeling fractions and proportions. The contribution of the paper is twofold. First, we extend the inflated beta regression model by allowing a regression structure for the precision parameter. We also present closed-form expressions for the score vector and Fisher's information matrix. Second, based on the proposed regression model, we introduce a new model-based control chart. The control limits are obtained considering the estimates of the inflated beta regression model parameters. We conduct a Monte Carlo simulation study to evaluate the performance of the proposed regression model estimators, and the performance of the proposed control chart is evaluated in terms of run length distribution. Finally, we present and discuss an empirical application to show the applicability of the proposed regression control chart.
- Subjects :
- Computer and Information Sciences
Statistical methods
Science
0211 other engineering and technologies
Control variable
Normal Distribution
02 engineering and technology
Linear Regression Analysis
01 natural sciences
Infographics
010104 statistics & probability
symbols.namesake
Statistics
Humans
Control chart
0101 mathematics
Fisher information
Beta distribution
Research Errors
Mathematics
Data Management
021103 operations research
Multidisciplinary
Models, Statistical
Data Visualization
Estimator
Regression analysis
Research Assessment
Probability Theory
Probability Distribution
Charts
Statistical Dispersion
Regression
Research and analysis methods
Monte Carlo method
Control limits
Data Interpretation, Statistical
Physical Sciences
symbols
Mathematical and statistical techniques
Regression Analysis
Medicine
Mathematical Functions
Research Article
Statistical Distributions
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....cd4ab2a8333dbde81d03df73fe5653df