estat comparereports fit statistics of the three transformations available in Procrustean analysis: orthogonal, oblique, and unrestricted. estat mvregreports the multivariate regression that is related to the c
A Multivariate Mathematical Morphology Based on Orthogonal Transformation, Probabilistic Extrema Estimation and Distance OptimizationMultivariate Mathematical MorphologyPrincipal Component AnalysisColor Image SegmentationMathematical morphology (MM) is a very popular image processing framework, which offers widely-used ...
Some upper bounds on the rate of convergence in the Central Limit Theorem for normalized least square estimators (LSE) in these regression models are obtained. The used method is based on the asymptotic analysis of orthogonal expansion of non linear functionals of stationary Gaussian processes and ...
Regression: Heckman selection model to reduce bias Multivariate Methods: Hotelling's T2 Discriminant analysis Mahalanobis’ distance Multivariate analysis of variance (MANOVA) and covariance (MANCOVA) Principal components analysis Factor analysis Cluster analysis Nonparametric Tests: Runs test Sign test Cochran...
Least absolute shrinkage and selection operator regression (LASSO) [18] is a multivariate embedded feature selection method. In a linear regression equation, the LASSO method adds a penalty term that discourages the model from assigning too much importance to any single feature. The penalty applied...
OPLS54 was used for the regression analyses using the detected proteins as regressors (X-variables). OPLS separates the systemic variation in X-variables into two parts; one part is correlated and predictive to Y-variable/variables and one is uncorrelated (orthogonal) to Y-variable/variables. ...
Multivariate Analysis 台湾交大統計學研究所 黃冠華老師 Prerequisite: Regression Analysis 教材:Applied Multivariate Statistical Analysis (6th Edition). Prentice HallJohnson, R.A. and Wichern, D.W., 2007. video/notes: http://ocw.nctu.edu.tw/course_detail-c.php?bgid=1&g 展开更多...
In this study, two artificial neural network models (i.e., a radial basis function neural network, RBFN, and an adaptive neurofuzzy inference system approach, ANFIS) and a multilinear regression (MLR) model were developed to simulate the DO, TP, Chl a, and SD in the Mingder Reservoir of...
In multivariate regression of Y on Z, the CS for Y|Z, represented by SY|Z, is defined as the intersection of all dimension-reduction subspaces S of Rp with the property Y⊥Z|PSZ, where PS is the orthogonal projection onto S in the usual inner product. SY|Z is an effective population...
A host of statistical tools are available to assist in analyzing large data sets, including regression analysis, cluster analysis, and principal component analysis, not only in the medical field, but also in finance, meteorology, astronomy and any other field in which the dimensionality of the rel...