書誌事項
- タイトル別名
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- Various Types of Nonparametric Transformation and Its Diagnosis
- ノンパラメトリック ヘンカン ノ ショケイ ト シンダン
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説明
In this paper, we introduce a Nonparametric Transform-Both-sides (NTB) approach as an alternative to the Power Transform-Both-sides (PTB) approach to inference for theoretical models and propose a method of parameter estimation by expressing the function transformation as a cubic spline curve. From the investigation of two examples, we suggest that the NTB could be an index for the validation of the PTB and is more robust than PTB to outliers. Furthermore, we verify these results by three simulation experiments. In the methodology for fitting the empirical model, we introduce Alternating Conditional Expectation (ACE) and Additivity VAriance Stabilization (AVAS) as two nonparametric transformation approaches that optimize the relationship between response and explanatory variables. We examine the validity of the theoretical models by fitting empirical models via ACE and AVAS to the example data. Both method, ACE and AVAS, improve the normality and homoscedasticity of the error.
収録刊行物
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- 応用統計学
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応用統計学 33 (1), 3-26, 2004
応用統計学会
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詳細情報 詳細情報について
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- CRID
- 1390001204442083072
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- NII論文ID
- 10013540262
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- NII書誌ID
- AN00330942
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- ISSN
- 18838081
- 02850370
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- NDL書誌ID
- 7075050
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可
