|
Useful Links |
|
|
Article Details :: |
|
|
| Article Name : | | | PLS COMPUTATIONAL MODEL FOR PREDICTION IN TIME SERIES | | Author Name : | | | S. Meenakshi Sundaram , M. Lakshmi | | Publisher : | | | Ashok Yakkaldevi | | Article Series No. : | | | GRT-3602 | | Article URL : | |  | Author Profile View PDF In browser | | Abstract : | | Some data fluctuates rapidly in a short period of time. Classical and computational models are useful in predicting this highly volatile data. In this study Partial Least Square Regression and computational neural network models are used to explore stock market tendency. Thirteen variables are considered to predict the daily closing prices of BSE sensex data. To evaluate the prediction ability of the models, standard error values are calculated. The results revealed that Nonparametric PLS regression model is better in prediction. naltrexone information go vivitrol uk | | Keywords : | | |
|
|