The LMSR method for providing a multidimensional understanding of growth standard in human fetuses
| Autor: | Hiroki Otani, Shouta Shimizu, Kanta Naito, Jun Udagawa |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
Penalized likelihood Multivariate statistics Epidemiology 030218 nuclear medicine & medical imaging Fetal Development Correlation 03 medical and health sciences 0302 clinical medicine Health Information Management Pregnancy Humans Mathematics 030219 obstetrics & reproductive medicine Anthropometry business.industry food and beverages Pattern recognition Nonlinear system Smooth curves Transformation (function) Skewness Multivariate Analysis Regression Analysis Female Artificial intelligence business Algorithms |
| Zdroj: | Statistical Methods in Medical Research. 27:2809-2830 |
| ISSN: | 1477-0334 0962-2802 |
| DOI: | 10.1177/0962280216687339 |
| Popis: | A new nonlinear multivariate regression method called the LMSR method is proposed, by which a multidimensional understanding for the development process of human fetuses can be provided. Statistically important quantities such as median, skewness, coefficient of variation, and correlation of underlying structure can be described by corresponding smooth curves. Those curves can be obtained by a fine combination of a multivariate power transformation of data and penalized likelihood. It will be shown that the LMSR method and some associated tools are clearly efficient in analyzing development process of human fetuses. |
| Databáze: | OpenAIRE |
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