Author(s)

Zerong Lin¹, Dongzhe Liu², Xueying Liu³, Lingling He¹, Changqing Xu^1*

¹School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, China.
²School of Energy and Environment, City University of Hong Kong, Hong Kong, China.
³Zhejiang University of Water Resources and Electric Power, Hang Zhou, China.

In this paper, we first study the linear regression model and obtain a norm-minimized estimator of the parameter vector by using the g-inverse and the singular value decomposition of matrix X. We then investigate the growth curve model (GCM) and extend the GCM to a generalized GCM (GGCM) by using high order tensors. The parameter estimations in GGCMs are also achieved in this way.

Tensor, Generalized Linear Model, Growth Curve Model, Parameter Estimation, Generalized Inverse

Lin, Z. , Liu, D. , Liu, X. , He, L. and Xu, C. (2018) High Order Tensor Forms of Growth Curve Models. Advances in Linear Algebra & Matrix Theory, 8, 18-32. doi: 10.4236/alamt.2018.81003.