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Chaouch, Mohamed; Khardani, Salah

Randomly censored quantile regression estimation using functional stationary ergodic data. (English) Zbl 1328.62276

J. Nonparametric Stat. 27, No. 1, 65-87 (2015).
Summary: This paper investigates the conditional quantile estimation of a randomly censored scalar response variable given a functional random covariate (i.e. valued in some infinite-dimensional space) whenever a stationary ergodic data are considered. A kernel-type estimator of the conditional quantile function is introduced. Then, a strong consistency rate as well as the asymptotic distribution of the estimator are established under mild assumptions. A simulation study is considered to show the performance of the proposed estimator. An application to the electricity peak demand prediction using censored smart meter data is also provided.

Cited in 20 Documents

MSC:

62G20 Asymptotic properties of nonparametric inference
62N01 Censored data models
62P30 Applications of statistics in engineering and industry; control charts
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)

Keywords:

asymptotic normality; censored data; conditional quantile; ergodic processes; functional data; peak load forecasting; strong consistency
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