頁籤選單縮合
題名 | Central Limit Theorems for Directional and Linear Random Variables with Applications |
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作 者 | García-Portugués, Eduardo; Crujeiras, Rosa M.; González-Manteiga, Wenceslao; | 書刊名 | Statistica Sinica |
卷期 | 25:3 2015.07[民104.07] |
頁次 | 頁1207-1229 |
分類號 | 319 |
關鍵詞 | Directional data; Goodness-of-fit; Independence test; Kernel density estimation; Limit distribution; |
語文 | 英文(English) |
英文摘要 | A central limit theorem for the integrated squared error of the directional-linear kernel density estimator is established. The result enables the construction and analysis of two testing procedures based on squared loss: a nonparametric independence test for directional and linear random variables and a goodness-of-fit test for parametric families of directional-linear densities. Limit distributions for both test statistics, and a consistent bootstrap strategy for the goodness-of-fit test, are developed for the directional-linear case and adapted to the directional-directional setting. Finite sample performance for the goodness-of-fit test is illustrated in a simulation study. This test is also applied to datasets from biology and environmental sciences. |
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