A Nonparametric Bootstrap Method for Heteroscedastic Functional Data
نویسندگان
چکیده
Abstract The objective is to provide a nonparametric bootstrap method for functional data that consists of independent realizations continuous one-dimensional process. process assumed be nonstationary, with mean and variance, dependent. resampling based on estimates the model components. Numerical studies were conducted check performance proposed procedure, by approximating bias standard error two estimators. A practical application approach pollution has also been included. Specifically, it employed make inference about annual trend ground-level ozone concentration at Yarner Wood monitoring station in United Kingdom. Supplementary material this paper provided online.
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ژورنال
عنوان ژورنال: Journal of Agricultural Biological and Environmental Statistics
سال: 2023
ISSN: ['1085-7117', '1537-2693']
DOI: https://doi.org/10.1007/s13253-023-00561-2