scholarly journals Gaussian Orthogonal Latent Factor Processes for Large Incomplete Matrices of Correlated Data

2022 ◽  
Vol -1 (-1) ◽  
Author(s):  
Mengyang Gu ◽  
Hanmo Li
Keyword(s):  
Correlated Data ◽  
Latent Factor

Quadratic Discriminant Analysis of Spatially Correlated Data

2001 ◽  
Vol 6 (2) ◽  
pp. 15-28 ◽  
Author(s):  
K. Dučinskas ◽  
J. Šaltytė
Keyword(s):  
Discriminant Function ◽  
Error Rate ◽  
Gaussian Random Field ◽  
Correlated Data ◽  
Covariance Matrices ◽  
Classification Rule ◽  
Spatial Correlations ◽  
Linear Quadratic ◽  
Spatial Correlation Function ◽  
Spatially Correlated

The problem of classification of the realisation of the stationary univariate Gaussian random field into one of two populations with different means and different factorised covariance matrices is considered. In such a case optimal classification rule in the sense of minimum probability of misclassification is associated with non-linear (quadratic) discriminant function. Unknown means and the covariance matrices of the feature vector components are estimated from spatially correlated training samples using the maximum likelihood approach and assuming spatial correlations to be known. Explicit formula of Bayes error rate and the first-order asymptotic expansion of the expected error rate associated with quadratic plug-in discriminant function are presented. A set of numerical calculations for the spherical spatial correlation function is performed and two different spatial sampling designs are compared.

scholarly journals Semiparametric time series models driven by latent factor

2021 ◽  
Author(s):  
Gisele de Oliveira Maia ◽  
Wagner Barreto-Souza ◽  
Fernando de Souza Bastos ◽  
Hernando Ombao
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Latent Factor
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