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國立臺灣大學計量理論與應用研究中心 (CRETA) 及臺灣經濟計量學會 (TES) 將於 2023 年 4 月 21 日舉辦 CRETA Seminar。相關資訊如下：
【 4 月 21 日 CRETA Seminar】
日期：2023 年 4 月 21 日 (週五) 下午 2:00~3:30
演講主題：Covariate adjusted functional principal component analysis
Principal component analysis is a classical dimension reduction tool in multivariate statistical analysis and its extension to functional data, termed Functional Principal Component Analysis (FPCA), plays a central role in the analysis of samples that are curves, functions, or surfaces. When additional covariates are available, three major models could be considered to accommodate them into the framework of FPCA. The first model integrates the covariates in the mean function only, and the second model integrates them in both the mean and the covariance function. However, the first model is not suitable for data that display second-order variation, while the second model makes it difficult to perform subsequent statistical analyses on the dimension-reduced representations in addition to being time-consuming. The third model was proposed to tackle these issues. Specifically, it assumes the covariance function varies with the covariates via its eigenvalues while the corresponding eigenfunctions remain independent of the covariates. In addition to briefly introducing the proposed estimators for all three models, I will use different real examples to demonstrate their performance.