Estimation of the parameters of the extended growth curve model under multivariate skew normal distribution

2018 ◽  
Vol 166 ◽  
pp. 111-128 ◽  
Author(s):  
Sayantee Jana ◽  
Narayanaswamy Balakrishnan ◽  
Jemila S. Hamid
Keyword(s):  
Normal Distribution ◽  
Growth Curve ◽  
Growth Curve Model ◽  
Skew Normal Distribution ◽  
Curve Model ◽  
Extended Growth Curve Model ◽  
Skew Normal

Inference in the Growth Curve Model under Multivariate Skew Normal Distribution

Sankhya B ◽  
2018 ◽  
Vol 82 (1) ◽  
pp. 34-69 ◽  
Author(s):  
Sayantee Jana ◽  
Narayanaswamy Balakrishnan ◽  
Jemila S. Hamid
Keyword(s):  
Normal Distribution ◽  
Growth Curve ◽  
Growth Curve Model ◽  
Skew Normal Distribution ◽  
Curve Model ◽  
Skew Normal

scholarly journals Estimation of parameters in the extended growth curve model with a linearly structured covariance matrix

2012 ◽  
Vol 16 (1) ◽  
pp. 13-32
Author(s):  
Joseph Nzabanita ◽  
Dietrich von Rosen ◽  
Martin Singull
Keyword(s):  
Covariance Matrix ◽  
Growth Curve ◽  
Estimation Procedure ◽  
Inner Product ◽  
Dispersion Matrix ◽  
Growth Curve Model ◽  
Estimation Of Parameters ◽  
Curve Model ◽  
Extended Growth Curve Model ◽  
Residual Space

In this paper the extended growth curve model with two terms and a linearly structured covariance matrix is considered. We propose an estimation procedure that handles linearly structured covariance matrices. The idea is first to estimate the covariance matrix when finding the inner product in a regression space and thereafter re-estimate it when it should be interpreted as a dispersion matrix. This idea is exploited by decomposing the residual space, the orthogonal complement to the design space, into three orthogonal subspaces. Studying residuals obtained from projections of observations on these subspaces yields explicit consistent estimators of the covariance matrix. An explicit consistent estimator of the mean is also proposed and numerical examples are given.

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