SEMIPARAMETRIC TRANSFORMATION FOR THEORETICAL MODEL

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概要

• 論文の詳細を見る

• For fitting any theoretical model, we introduce the Power Transform-Both-sides (PTB) approach and the Power Transform-Both-sides and Weighted Least Squares (PTBWLS) approach which implements a power weighted transformation approach in PTB. Then, as an alternative to the PTB, we provide a Nonparametric Transform-Both-sides (NTB) approach to express function transformation as a cubic spline curve. As an estimation method which combines PTBWLS with together NTB, we propose a Nonparametric Transform-Both-sides and Weighted Least Squares (NTBWLS) approach. Through the numerical investigation of one example using data generated from a 1-compartment model, we conclude that PTB and PTBWLS induce normally distributed additive errors and stabilize the error variance, and NTBWLS improves the degrees of normality and homoscedasticity of the error more than PTB and PTBWLS.

• 日本計算機統計学会の論文

著者

• GOTO Masashi

  Biostatistical Research Association

• Goto Masashi

  Biostatistical Research Association Non Profit Organization

• Ito Masanori

  Data Science Department, Astellas Pharma Inc.

• Ito Masanori

  Data Science Department Astellas Pharma Inc.

関連論文

• ESTIMATION FROM PSEUDO PARTIAL LIKELIHOOD IN A SEMIPARAMETRIC CURE MODEL
• ASYMPTOTIC PROPERTIES OF ESTIMATES OF THE POWER-TRANSFORMATION MODEL TO BIVARIATE GROUPED DATA
• BOX AND COX POWER-TRANSFORMATION TO ADDITIVITY AND HOMOSCEDASTICITY IN REGRESSION
• UNDERLYING ASSUMPTIONS OF THE POWER-NORMAL DISTRIBUTION
• SEMIPARAMETRIC TRANSFORMATION FOR THEORETICAL MODEL
• HIERARCHICAL CLUSTER ANALYSIS FOR MULTI-SAMPLE COMPARISONS BASED ON THE POWER-NORMAL DISTRIBUTION

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