功能数据分析和非线性回归模型:信息质量视角

IF 1.3 4区工程技术 Q4 ENGINEERING, INDUSTRIAL

Quality Engineering Pub Date : 2023-01-03 DOI:10.1080/08982112.2022.2153696

R. Kenett, C. Gotwalt

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引用次数: 1

摘要

摘要随时间变化的测量数据可以通过不同的方式进行分析。在本文中，我们比较了函数数据分析和非线性回归模型，其中使用了八个信息质量维度。我们介绍了两个案例研究。第一个案例研究介绍了功能数据分析和非线性回归模型，用于分析片剂的溶出度分布，其中将受试片剂的分布与对照片剂的分布进行比较。第二个案例研究涉及用于优化片剂配方的统计设计的混合物实验。Python和JMP特性用于演示两个案例研究中使用的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Functional data analysis and nonlinear regression models: an information quality perspective

Abstract Data from measurements over time can be analyzed in different ways. In this article, we compare functional data analysis and nonlinear regression models using, among others, eight information quality dimensions. We present two case studies. The first case study introduces functional data analysis and nonlinear regression models in analyzing dissolution profiles of drug tablets where profiles of tablets under test are compared to reference tablets. A second case study involves statistically designed mixture experiments used in optimization tablet formulation. Python and JMP features are used to demonstrate the methods used in the two case studies.

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来源期刊

Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY

CiteScore

3.90

自引率

10.00%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.