The Size Problem of Bootstrap Tests when the Null is Non- or Semiparametric

被引：0

作者：

Barrientos-Marin, Jorge ^{[1
]}

Sperlich, Stefan ^{[2
]}

机构：

[1] Univ Antioquia, Fac Ciencias Econ, Dept Econ, Medellin, Colombia

[2] Univ Gottingen, Inst Stat & Okonometrie, Gottingen, Germany

来源：

REVISTA COLOMBIANA DE ESTADISTICA | 2010年 / 33卷 / 02期

关键词：

Bandwidth choice; Bootstrap tests; Nonparametric specification tests; INFERENCE;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In non- and semiparametric testing, the wild bootstrap is a standard method for determining the critical values of tests. If the null hypothesis is also semi- or nonparametric, then we know that at least asymptotically oversmoothing is necessary in the pre-estimation of the null model for generating the bootstrap samples. See Hardle & Marron (1990, 1991). However, in practice this knowledge is of little help. In this note we highlight that this bandwidth choice problem can become quite serious. As an alternative, we briegly discuss the possibility of subsampling.(1)

引用

页码：307 / 319

页数：13

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