The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 13 Mar 2018|
|Event||2nd International Conference on Science, ICOS 2017 - Makassar, Indonesia|
Duration: 2 Nov 2017 → 3 Nov 2017