Abstract
The purpose of the present study was to establish an extension of generalized tri-phasic logistic human growth model. This model was applied through the higher dimensional growth process. Bayesian method of estimation was applied to estimate the parameters of the model. Principal component regression method was applied when there was a problem of multicollinearity in the model. The biological characteristics of the human growth process were extracted from the velocity and acceleration curve using gradient vector and Hessian matrix.
Highlights
Growth modeling is very important in recent time for the purpose of the study of growth pattern and biological characteristics
Bock-Thissen-du Toit (BTT) [18] model is found to be better than JPA-2 model
The proposed extension of BTT model is very important because the stature of human depends on several factors
Summary
Growth modeling is very important in recent time for the purpose of the study of growth pattern and biological characteristics. Most of the growth models such as Gompertz and the logistic growth model [1,2], Jenss model [3], Count model [4,5] , Double logistic model [6], PB models [7,8], ICP model [9], Reed models [10], SSC model [8,11], JPPS model [12], JPA-1 and JPA-2 model [13], Modified ICP model [14], BTT model [15] have considered stature or weight as a function of age. The JPA-2 [13] model fits better than all other asymptotic models till 1991. BTT [18] model is found to be better than JPA-2 model. It is important to incorporate other possible predictors in the model as they have significant influence on stature, the influence of age on stature is higher than others predictors
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