1
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Lin L, Li F. Global debiased DC estimations for biased estimators via pro forma regression. TEST-SPAIN 2023. [DOI: 10.1007/s11749-023-00850-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
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2
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Kai B, Huang M, Yao W, Dong Y. Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm. J Comput Graph Stat 2023. [DOI: 10.1080/10618600.2023.2184374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Affiliation(s)
- Bo Kai
- Department of Mathematics, College of Charleston
| | - Mian Huang
- School of Statistics and Management, Shanghai University of Finance and Economics
| | - Weixin Yao
- Department of Statistics, University of California, Riverside
| | - Yuexiao Dong
- Department of Statistics, Operations, and Data Science, Temple University
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3
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Extreme partial least-squares. J MULTIVARIATE ANAL 2022. [DOI: 10.1016/j.jmva.2022.105101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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4
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Hlubinka D, Kotík L, Šiman M. Multivariate Quantiles with Both Overall and Directional Probability Interpretation. Scand Stat Theory Appl 2022. [DOI: 10.1111/sjos.12603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Daniel Hlubinka
- Univerzita Karlova Matematicko‐fyzikální fakulta, Department of Probability and Statistics
| | | | - Miroslav Šiman
- Institute of Information Theory and Automation Czech Academy of Sciences
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5
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Dorn J, Guo K. Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing. J Am Stat Assoc 2022. [DOI: 10.1080/01621459.2022.2069572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Jacob Dorn
- Department of Economics, Princeton University
| | - Kevin Guo
- Department of Statistics, Stanford University
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Affiliation(s)
- Xingyu Zhou
- Department of Statistics and Actuarial Science, University of Iowa, Iowa City, Iowa 52242, USA
| | - Yuling Jiao
- School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China 430072
| | - Jin Liu
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore
| | - Jian Huang
- Department of Statistics and Actuarial Science, University of Iowa, Iowa City, Iowa 52242, USA
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7
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Zhou Y, Ma C, Li D, He F. Estimation in quantile regression models with jump discontinuities. COMMUN STAT-THEOR M 2021. [DOI: 10.1080/03610926.2020.1728556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Yuejin Zhou
- Department of Statistics, Anhui University of Science and Technology, Huainan, China
| | - Chi Ma
- Department of Statistics, Anhui University of Science and Technology, Huainan, China
| | - Dequan Li
- Department of Statistics, Anhui University of Science and Technology, Huainan, China
| | - Fengyang He
- Department of Statistics, Jinan University, Guangzhou, China
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8
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Uniform consistency in number of neighbors of the kNN estimator of the conditional quantile model. METRIKA 2021. [DOI: 10.1007/s00184-021-00806-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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9
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Labopin-Richard T, Gamboa F, Garivier A, Stenger J. Conditional Quantile Sequential Estimation for Stochastic Codes. JOURNAL OF STATISTICAL THEORY AND PRACTICE 2019. [DOI: 10.1007/s42519-019-0053-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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10
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Affiliation(s)
- Kyunghee Han
- Department of Statistics, University of California, Davis
| | | | - Byeong U. Park
- Department of Statistics, Seoul National University, Seoul, Republic of Korea
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Affiliation(s)
- Jaeoh Kim
- Department of Statistics, Korea University, Seoul, Republic of Korea
| | - HyungJun Cho
- Department of Statistics, Korea University, Seoul, Republic of Korea
| | - Sungwan Bang
- Department of Mathematics, Korea Military Academy, Seoul, Republic of Korea
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Ma S, He X. Inference for single-index quantile regression models with profile optimization. Ann Stat 2016. [DOI: 10.1214/15-aos1404] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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16
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Charlier I, Paindaveine D, Saracco J. Conditional quantile estimation based on optimal quantization: From theory to practice. Comput Stat Data Anal 2015. [DOI: 10.1016/j.csda.2015.05.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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17
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Horrigue W, Saïd EO. Non Parametric Regression Quantile Estimation for Dependent Functional Data under Random Censorship: Asymptotic Normality. COMMUN STAT-THEOR M 2015. [DOI: 10.1080/03610926.2013.784993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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18
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19
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Hallin M, Lu Z, Paindaveine D, Šiman M. Local bilinear multiple-output quantile/depth regression. BERNOULLI 2015. [DOI: 10.3150/14-bej610] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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20
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Charlier I, Paindaveine D, Saracco J. Conditional quantile estimation through optimal quantization. J Stat Plan Inference 2015. [DOI: 10.1016/j.jspi.2014.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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21
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22
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Sun J, Liao H, Upadhyaya BR. A robust functional-data-analysis method for data recovery in multichannel sensor systems. IEEE TRANSACTIONS ON CYBERNETICS 2014; 44:1420-1431. [PMID: 25051452 DOI: 10.1109/tcyb.2013.2285876] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Multichannel sensor systems are widely used in condition monitoring for effective failure prevention of critical equipment or processes. However, loss of sensor readings due to malfunctions of sensors and/or communication has long been a hurdle to reliable operations of such integrated systems. Moreover, asynchronous data sampling and/or limited data transmission are usually seen in multiple sensor channels. To reliably perform fault diagnosis and prognosis in such operating environments, a data recovery method based on functional principal component analysis (FPCA) can be utilized. However, traditional FPCA methods are not robust to outliers and their capabilities are limited in recovering signals with strongly skewed distributions (i.e., lack of symmetry). This paper provides a robust data-recovery method based on functional data analysis to enhance the reliability of multichannel sensor systems. The method not only considers the possibly skewed distribution of each channel of signal trajectories, but is also capable of recovering missing data for both individual and correlated sensor channels with asynchronous data that may be sparse as well. In particular, grand median functions, rather than classical grand mean functions, are utilized for robust smoothing of sensor signals. Furthermore, the relationship between the functional scores of two correlated signals is modeled using multivariate functional regression to enhance the overall data-recovery capability. An experimental flow-control loop that mimics the operation of coolant-flow loop in a multimodular integral pressurized water reactor is used to demonstrate the effectiveness and adaptability of the proposed data-recovery method. The computational results illustrate that the proposed method is robust to outliers and more capable than the existing FPCA-based method in terms of the accuracy in recovering strongly skewed signals. In addition, turbofan engine data are also analyzed to verify the capability of the proposed method in recovering non-skewed signals.
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23
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Zhao Z, Wei Y, Lin DKJ. Asymptotics of nonparametric L-1 regression models with dependent data. BERNOULLI 2014; 20:1532-1559. [PMID: 24955016 DOI: 10.3150/13-bej532] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially correlated data, we establish uniform Bahadur representations for the proposed median quantile estimates. The obtained Bahadur representations provide deep insights into the asymptotic behavior of the estimates. Our main theoretical development is based on studying the modulus of continuity of kernel weighted empirical process through a coupling argument. Progesterone data is used for an illustration.
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Affiliation(s)
- Zhibiao Zhao
- Department of Statistics, Penn State University, University Park, PA 16802
| | - Ying Wei
- Department of Biostatistics, Columbia University, 722 West 168th St., New York, NY 10032
| | - Dennis K J Lin
- Department of Statistics, Penn State University, University Park, PA 16802
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24
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Enss GC, Götz B, Kohler M, Krzyżak A, Platz R. Nonparametric estimation of a maximum of quantiles. Electron J Stat 2014. [DOI: 10.1214/14-ejs970] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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25
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Efficient simulation of complete and censored samples from common bivariate exponential distributions. Comput Stat 2013. [DOI: 10.1007/s00180-013-0415-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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26
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Oh HS, Lee TCM, Nychka DW. Fast Nonparametric Quantile Regression With Arbitrary Smoothing Methods. J Comput Graph Stat 2011. [DOI: 10.1198/jcgs.2010.10063] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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27
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Horrigue W, Saïd EO. Strong uniform consistency of a nonparametric estimator of a conditional quantile for censored dependent data and functional regressors. RANDOM OPERATORS AND STOCHASTIC EQUATIONS 2011. [DOI: 10.1515/rose.2011.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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28
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Kyung Lee Y, Ryung Lee E, Park BU. Conditional quantile estimation by local logistic regression. J Nonparametr Stat 2010. [DOI: 10.1080/10485250601014248] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Young Kyung Lee
- a Department of Statistics , Seoul National University , Seoul, 151-747, Korea
| | - Eun Ryung Lee
- a Department of Statistics , Seoul National University , Seoul, 151-747, Korea
| | - Byeong U. Park
- a Department of Statistics , Seoul National University , Seoul, 151-747, Korea
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29
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Park C, Lee TCM, Hannig J. Multiscale Exploratory Analysis of Regression Quantiles Using Quantile SiZer. J Comput Graph Stat 2010. [DOI: 10.1198/jcgs.2010.09120] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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31
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32
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Lemdani M, Ould-Saïd E, Poulin N. Asymptotic properties of a conditional quantile estimator with randomly truncated data. J MULTIVARIATE ANAL 2009. [DOI: 10.1016/j.jmva.2008.06.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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33
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Draghicescu D, Guillas S, Wu WB. Quantile Curve Estimation and Visualization for Nonstationary Time Series. J Comput Graph Stat 2009. [DOI: 10.1198/jcgs.2009.0001] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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34
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Ezzahrioui M, Ould-Saïd E. Asymptotic Results of a Nonparametric Conditional Quantile Estimator for Functional Time Series. COMMUN STAT-THEOR M 2008. [DOI: 10.1080/03610920802001870] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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35
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Kokic PN, Moon L, Gooday J, Chambers RL. ESTIMATING TEMPORAL FARM INCOME DISTRIBUTIONS USING SPATIAL SMOOTHING TECHNIQUES. ACTA ACUST UNITED AC 2008. [DOI: 10.1111/j.1467-842x.1995.tb00647.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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36
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Hallin M, Vermandele C, Werker BJM. Semiparametrically efficient inference based on signs and ranks for median-restricted models. J R Stat Soc Series B Stat Methodol 2008. [DOI: 10.1111/j.1467-9868.2007.00641.x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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37
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39
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41
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ESTIMATION, INFERENCE, AND SPECIFICATION TESTING FOR POSSIBLY MISSPECIFIED QUANTILE REGRESSION. MAXIMUM LIKELIHOOD ESTIMATION OF MISSPECIFIED MODELS: TWENTY YEARS LATER 2004. [DOI: 10.1016/s0731-9053(03)17005-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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42
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Yu K, Lu Z, Stander J. Quantile regression: applications and current research areas. ACTA ACUST UNITED AC 2003. [DOI: 10.1111/1467-9884.00363] [Citation(s) in RCA: 259] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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43
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Hall P, Müller HG. Order-Preserving Nonparametric Regression, With Applications to Conditional Distribution and Quantile Function Estimation. J Am Stat Assoc 2003. [DOI: 10.1198/016214503000000512] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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44
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Hong SY. Bahadur representation and its applications for local polynomial estimates in nonparametric M -regression. J Nonparametr Stat 2003. [DOI: 10.1080/1048525031000089275] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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45
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Zhou Y, Liang H. Asymptotic properties for l 1 norm kernel estimator of conditional median under dependence. J Nonparametr Stat 2003. [DOI: 10.1080/1048525031000089293] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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46
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Gannoun A, Girard S, Guinot C, Saracco J. Reference curves based on non-parametric quantile regression. Stat Med 2002; 21:3119-35. [PMID: 12369086 DOI: 10.1002/sim.1226] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Reference curves which take time into account, such as those for age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). Semi-parametric methods are also widely used especially in Europe. Here, we propose a new methodology for the estimation of reference intervals for data sets, based on non-parametric estimation of conditional quantiles. The derived methods should be applicable to all clinical (or more generally biological) variables that are measured on a continuous quantitative scale. As an example, we analyse a data set collected to establish reference curves for biophysical properties of the skin of healthy French women. The results are compared to those obtained with Royston's polynomial parametric method and the semi-parametric LMS approach.
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Affiliation(s)
- Ali Gannoun
- Laboratoire de Probabilités et Statistique, Université Montpellier II, Place Eugène Bataillon, 34095 Montpellier Cedex 5, France.
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47
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Polonik W, Yao Q. Set-Indexed Conditional Empirical and Quantile Processes Based on Dependent Data. J MULTIVARIATE ANAL 2002. [DOI: 10.1006/jmva.2001.1988] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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48
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49
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50
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Frank Marohn MF. Efficient estimation in local parametric regression analysis. COMMUN STAT-THEOR M 2000. [DOI: 10.1080/03610920008832611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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