International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 103 | Views: 195

Research Paper | Mathematics | Kenya | Volume 3 Issue 6, June 2014 | Rating: 6.2 / 10


Comparative Study of Performance of Neural Networks with Other Non-Parametric Regression Estimators

Robert Kasisi [2]


Abstract: Neural Neural networks have drawn attention to researchers in recent years. This is because they show superiority as a modeling technique for datasets showing nonlinear relationships and thus for both data fitting and prediction abilities. In this study we derive a neural network estimator of finite population mean. This study shows that the mean square error values of the neural network estimator are minimal compared to those of other nonparametric estimators. This implies that neural networks are a better estimation technique for estimating population mean.


Keywords: Neural networks, nonlinear model, nonparametric regression, auxiliary information, survey sampling


Edition: Volume 3 Issue 6, June 2014,


Pages: 1291 - 1294

Rate this Article


Select Rating (Lowest: 1, Highest: 10)

5

Your Comments

Characters: 0


Type Your Registered Email Address below to Rate the Article


Verification Code will appear in 2 Seconds ... Wait

Top