本文是笔者学习函数型的数据 (functional data)的笔记 ,主要参考了这篇文献 WANG, J.-L., CHIOU, J.-M. and MÜLLER, H.-G. (2016). Review of functional data analysis. Ann. Rev. Statist. Appl. 3 257–295. 中的相关内容,是关键思想的总结而不太注重技术
主要的方法: 1.分析函数型数据时常用的statistic或heuristic 2.光滑函数建模优化再提取特征(主要是spline做基函数,还有wavelet之类的) 3.registration 4.PCA 5.functional linear model 还会补充看一些regression的方法,但我不知道咋归类了,还不是很了解 ...
Spatio-functional data analysis (sFDA)Expected Shortfall (ES)Value-at-Risk (VaR)Expectile regressionRisk measuresARCH processThis paper deals with the nonparametric estimation of the expectile regression when the observations are spatially correlated and are of a functional nature. The main findings of ...
This interpretation can be used in the analysis of scalograms from regression and classification models. For instance, B-coefficient vectors used in regression and decision planes in multivariate discrimination can be displayed as scalograms. Variables in the scalogram that are identified as particular...
内容简介· ··· Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and ...
Scientists and others today often collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modeling, and canon...
Presents new nonparametric statistical methods for functional regression analysis, including Gaussian process functional regression (GPFR) models, mixture GPFR models, and generalized GPFR models Covers various topics in functional data analysis, including curve prediction, curve clustering, and functional AN...
Includes a wide range of utils to work with functional data, and its representation, exploratory analysis, or preprocessing, among other tasks such as inference, classification, regression or clustering of functional data. See documentation for further information on the features included in the ...
Representing Functional Data: Smoothing Penalties Linear Regression on Basis Functions If the N by K matrix Φ contains the values φ j (t k ), and y is the vector (y 1 , . . . , y N ), we can write SSE(c) = (y −Φc) T (y −Φc) The error sum of squares is minim...
Gaussian Process Functional Regression Modeling for Batch Data A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultane... JQ Shi,B Wang,MSM Titterington - 《Biometrics》 被引量: 110发表: 2007年 Curve...