The Akaike information criterion in weighted regression of immittance data

被引：23

作者：

Ingdal, Mats ^{[1
]}

Johnsen, Roy ^{[1
]}

Harrington, David A. ^{[2
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Mech & Ind Engn, N-7491 Trondheim, Norway

[2] Univ Victoria, Dept Chem, Victoria, BC V8W 2Y2, Canada

来源：

ELECTROCHIMICA ACTA | 2019年 / 317卷

关键词：

Akaike information criterion; Weighted regression; Error structure; Impedance; Maximum likelihood; ELECTROCHEMICAL IMPEDANCE; MODELS; SPECTROSCOPY; MEMBRANE;

D O I：

10.1016/j.electacta.2019.06.030

中图分类号：

O646 [电化学、电解、磁化学];

学科分类号：

081704 ;

摘要：

The Akaike Information Criterion (AIC) is a powerful way to distinguish between models. It considers both the goodness-of-fit and the number of parameters in the model, but has been little used for immittance data. Application in the case of weighted complex nonlinear least squares regression, as typically used in fitting impedance or admittance data, is considered here. AIC can be used to compare different weighting schemes as well as different models. These ideas are tested for simulated and real transadmittance data for hydrogen diffusion through an iron foil in a Devanathan-Stachurski cell. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：648 / 653

页数：6

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