Input modeling using quantile statistical methods

被引:0
|
作者
Gupta, A [1 ]
Parzen, E [1 ]
机构
[1] Texas A&M Univ, Dept Ind Engn, College Stn, TX 77843 USA
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper applies quantile data analysis to input modeling in simulation. We introduce the use of QIQ plots to identify suitable distributions fitting the data and comparison distribution P-P plots to test the fit. Two examples illustrate the utility of these quantile statistical methods for input modeling. Popular distribution fitting software often give confusing results, which is usually a set of distributions differing marginally in the test statistic value. The methods discussed in this paper can be used for further analysis of the software results.
引用
收藏
页码:728 / 736
页数:9
相关论文
共 50 条
  • [1] Quantile probability and statistical data modeling
    Parzen, E
    STATISTICAL SCIENCE, 2004, 19 (04) : 652 - 662
  • [2] Extreme Rainfall Prediction using Bayesian Quantile Regression in Statistical Downscaling Modeling
    Rachmawati, Ro'fah Nur
    Sungkawa, Iwa
    Rahayu, Anita
    4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND COMPUTATIONAL INTELLIGENCE (ICCSCI 2019) : ENABLING COLLABORATION TO ESCALATE IMPACT OF RESEARCH RESULTS FOR SOCIETY, 2019, 157 : 406 - 413
  • [3] Statistical Downscaling Modeling With Quantile Regression Using Lasso To Estimate Extreme Rainfall
    Santri, Dewi
    Wigena, Aji Hamim
    Djuraidah, Anik
    PROCEEDINGS OF THE 7TH SEAMS UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2015: ENHANCING THE ROLE OF MATHEMATICS IN INTERDISCIPLINARY RESEARCH, 2016, 1707
  • [4] MODELING ARABIC LANGUAGE USING STATISTICAL METHODS
    Meftouh, Karima
    Laskri, M. Tayeb
    Smaili, Kamel
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2010, 35 (2C) : 69 - 82
  • [5] Input variable scaling for statistical modeling
    Kim, Sanghong
    Kano, Manabu
    Nakagawa, Hiroshi
    Hasebe, Shinji
    COMPUTERS & CHEMICAL ENGINEERING, 2015, 74 : 59 - 65
  • [6] Predictive Resilience Modeling Using Statistical Regression Methods
    Silva, Priscila
    Hidalgo, Mariana
    Hotchkiss, Mindy
    Dharmasena, Lasitha
    Linkov, Igor
    Fiondella, Lance
    MATHEMATICS, 2024, 12 (15)
  • [7] Resampling methods for input modeling
    Barton, RR
    Schruben, LW
    WSC'01: PROCEEDINGS OF THE 2001 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2001, : 372 - 378
  • [8] Statistical downscaling of precipitation using quantile regression
    Tareghian, Reza
    Rasmussen, Peter F.
    JOURNAL OF HYDROLOGY, 2013, 487 : 122 - 135
  • [9] MODELING STUDENT DROPOUT USING STATISTICAL AND DATA MINING METHODS
    Berka, Petr
    Marek, Lubos
    Vrabec, Michal
    PROCEEDINGS OF THE 22ND INTERNATIONAL SCIENTIFIC CONFERENCE ON APPLICATIONS OF MATHEMATICS AND STATISTICS IN ECONOMICS (AMSE 2019), 2019, : 70 - 80
  • [10] METHODS FOR STATISTICAL DETERMINATION OF EFFECTIVE INPUT VARIABLES
    VAURIO, JK
    TRANSACTIONS OF THE AMERICAN NUCLEAR SOCIETY, 1979, 32 (JUN): : 296 - 297