Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/axioms10030154 |
Water Particles Monitoring in the Atacama Desert: SPC Approach Based on Proportional Data | |
Fonseca, Anderson; Ferreira, Paulo Henrique; do Nascimento, Diego Carvalho; Fiaccone, Rosemeire; Ulloa-Correa, Christopher; Garcia-Pina, Ayon; Louzada, Francisco | |
通讯作者 | Ferreira, PH (corresponding author), Univ Fed Bahia, Dept Stat, BR-40170110 Salvador, BA, Brazil. |
来源期刊 | AXIOMS
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EISSN | 2075-1680 |
出版年 | 2021 |
卷号 | 10期号:3 |
英文摘要 | Statistical monitoring tools are well established in the literature, creating organizational cultures such as Six Sigma or Total Quality Management. Nevertheless, most of this literature is based on the normality assumption, e.g., based on the law of large numbers, and brings limitations towards truncated processes as open questions in this field. This work was motivated by the register of elements related to the water particles monitoring (relative humidity), an important source of moisture for the Copiapo watershed, and the Atacama region of Chile (the Atacama Desert), and presenting high asymmetry for rates and proportions data. This paper proposes a new control chart for interval data about rates and proportions (symbolic interval data) when they are not results of a Bernoulli process. The unit-Lindley distribution has many interesting properties, such as having only one parameter, from which we develop the unit-Lindley chart for both classical and symbolic data. The performance of the proposed control chart is analyzed using the average run length (ARL), median run length (MRL), and standard deviation of the run length (SDRL) metrics calculated through an extensive Monte Carlo simulation study. Results from the real data applications reveal the tool's potential to be adopted to estimate the control limits in a Statistical Process Control (SPC) framework. |
英文关键词 | Symbolic Data Analysis (SDA) in Statistical Process Control (SPC) rates and proportions data unit-Lindley distribution relative air humidity monitoring Monte Carlo simulation |
类型 | Article |
语种 | 英语 |
开放获取类型 | gold |
收录类别 | SCI-E |
WOS记录号 | WOS:000699214400001 |
WOS关键词 | CONTROL CHART ; REGRESSION ; RESOURCE |
WOS类目 | Mathematics, Applied |
WOS研究方向 | Mathematics |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/362685 |
作者单位 | [Fonseca, Anderson; Ferreira, Paulo Henrique; Fiaccone, Rosemeire] Univ Fed Bahia, Dept Stat, BR-40170110 Salvador, BA, Brazil; [do Nascimento, Diego Carvalho] Univ Atacama, Fac Ingn, Dept Matemat, Copiapo 1530000, Chile; [Ulloa-Correa, Christopher; Garcia-Pina, Ayon] Univ Atacama, Lab Invest Criosfera & Aguas, IDICTEC, Copiapo 1530000, Chile; [Louzada, Francisco] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, Brazil |
推荐引用方式 GB/T 7714 | Fonseca, Anderson,Ferreira, Paulo Henrique,do Nascimento, Diego Carvalho,et al. Water Particles Monitoring in the Atacama Desert: SPC Approach Based on Proportional Data[J],2021,10(3). |
APA | Fonseca, Anderson.,Ferreira, Paulo Henrique.,do Nascimento, Diego Carvalho.,Fiaccone, Rosemeire.,Ulloa-Correa, Christopher.,...&Louzada, Francisco.(2021).Water Particles Monitoring in the Atacama Desert: SPC Approach Based on Proportional Data.AXIOMS,10(3). |
MLA | Fonseca, Anderson,et al."Water Particles Monitoring in the Atacama Desert: SPC Approach Based on Proportional Data".AXIOMS 10.3(2021). |
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