Oracally efficient estimation for dense functional data with holiday effects
被引:6
作者:
Cai, Li
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Zhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R ChinaZhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
Cai, Li
[1
]
Li, Lisha
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Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R ChinaZhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
Li, Lisha
[2
]
Huang, Simin
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Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R ChinaZhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
Huang, Simin
[2
]
Ma, Liang
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Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R ChinaZhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
Ma, Liang
[2
]
Yang, Lijian
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Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R China
Tsinghua Univ, Ctr Stat Sci, Beijing, Peoples R ChinaZhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
Yang, Lijian
[2
,3
]
机构:
[1] Zhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Peoples R China
[2] Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R China
[3] Tsinghua Univ, Ctr Stat Sci, Beijing, Peoples R China
Existing functional data analysis literature has mostly overlooked data with spikes in mean, such as weekly sporting goods sales by a salesperson which spikes around holidays. For such functional data, two-step estimation procedures are formulated for the population mean function and holiday effect parameters, which correspond to the population sales curve and the spikes in sales during holiday times. The estimators are based on spline smoothing for individual trajectories using non-holiday observations, and are shown to be oracally efficient in the sense that both the mean function and holiday effects are estimated as efficiently as if all individual trajectories were known a priori. Consequently, an asymptotic simultaneous confidence band is established for the mean function and confidence intervals for holiday effects, respectively. Two sample extensions are also formulated and simulation experiments provide strong evidence that corroborates the asymptotic theory. Application to sporting goods sales data has led to a number of new discoveries.
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页码:282 / 306
页数:25
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Univ Toledo, Dept Math & Stat, Toledo, OH 43006 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Liu, Rong
Wang, Suojin
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Texas A&M Univ, Dept Stat, College Stn, TX 77843 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
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Tsinghua Univ, Ctr Stat Sci, Beijing 100084, Peoples R China
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R ChinaSoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
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Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Cao, Guanqun
Yang, Lijian
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Soochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
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Todem, David
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Michigan State Univ, Dept Epidemiol, Div Biostat, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
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Univ Toledo, Dept Math & Stat, Toledo, OH 43006 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Liu, Rong
Wang, Suojin
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Texas A&M Univ, Dept Stat, College Stn, TX 77843 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Wang, Suojin
Yang, Lijian
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Tsinghua Univ, Ctr Stat Sci, Beijing 100084, Peoples R China
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R ChinaSoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
机构:
Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Cao, Guanqun
Yang, Lijian
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Soochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China
Yang, Lijian
Todem, David
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Michigan State Univ, Dept Epidemiol, Div Biostat, E Lansing, MI 48824 USASoochow Univ, Ctr Adv Stat & Econometr Res, Suzhou 215006, Peoples R China