MODEL SELECTION IN NEURAL NETWORKS BY USING INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION FOR TIME SERIES FORCASTING
Abstract. The aim of this paper is to discuss and propose a procedure for model selection in neural network for time series forecasting. We focus on the model selection strategies based on statistical concept, particularly on the inference of R2 incremental, Principal Component Analysis (PCA) of t...
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| Format: | Article |
| Language: | English |
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2006
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| Online Access: | https://repository.ugm.ac.id/32902/1/1.pdf |
| _version_ | 1797020193644347392 |
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| author | Suhartono, Suhartono Subanar, Subanar Suryo , Guritno |
| author_facet | Suhartono, Suhartono Subanar, Subanar Suryo , Guritno |
| author_sort | Suhartono, Suhartono |
| collection | UGM |
| description | Abstract. The aim of this paper is to discuss and propose a procedure for model selection
in neural network for time series forecasting. We focus on the model selection strategies based on statistical concept, particularly on the inference of R2 incremental, Principal Component Analysis (PCA) of the residual model and SIC criterion. In this paper, we
employ this new procedure in two main approaches for model selection in neural networks, those are bottom-up or forward approach which starts with a large neural networks and top-down or backward approach which begins with an empty model. We use simulation as case study. The result show that statistical inference of R2 incremental combined with SIC criterion is an an effective procedure for model selection in neural networks for time series forecasting.
Key words: Neural network, model selection, statistical inference, time series forecasting |
| first_indexed | 2024-03-05T23:19:47Z |
| format | Article |
| id | oai:generic.eprints.org:32902 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-13T19:12:13Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:329022016-02-18T04:35:03Z https://repository.ugm.ac.id/32902/ MODEL SELECTION IN NEURAL NETWORKS BY USING INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION FOR TIME SERIES FORCASTING Suhartono, Suhartono Subanar, Subanar Suryo , Guritno Statistics Abstract. The aim of this paper is to discuss and propose a procedure for model selection in neural network for time series forecasting. We focus on the model selection strategies based on statistical concept, particularly on the inference of R2 incremental, Principal Component Analysis (PCA) of the residual model and SIC criterion. In this paper, we employ this new procedure in two main approaches for model selection in neural networks, those are bottom-up or forward approach which starts with a large neural networks and top-down or backward approach which begins with an empty model. We use simulation as case study. The result show that statistical inference of R2 incremental combined with SIC criterion is an an effective procedure for model selection in neural networks for time series forecasting. Key words: Neural network, model selection, statistical inference, time series forecasting 2006-06-01 Article PeerReviewed application/pdf en https://repository.ugm.ac.id/32902/1/1.pdf Suhartono, Suhartono and Subanar, Subanar and Suryo , Guritno (2006) MODEL SELECTION IN NEURAL NETWORKS BY USING INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION FOR TIME SERIES FORCASTING. QUANTITATIVE METHODS, 2 (1). pp. 9-20. ISSN 1693 5098 |
| spellingShingle | Statistics Suhartono, Suhartono Subanar, Subanar Suryo , Guritno MODEL SELECTION IN NEURAL NETWORKS BY USING INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION FOR TIME SERIES FORCASTING |
| title | MODEL SELECTION IN NEURAL NETWORKS BY USING
INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION
FOR TIME SERIES FORCASTING |
| title_full | MODEL SELECTION IN NEURAL NETWORKS BY USING
INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION
FOR TIME SERIES FORCASTING |
| title_fullStr | MODEL SELECTION IN NEURAL NETWORKS BY USING
INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION
FOR TIME SERIES FORCASTING |
| title_full_unstemmed | MODEL SELECTION IN NEURAL NETWORKS BY USING
INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION
FOR TIME SERIES FORCASTING |
| title_short | MODEL SELECTION IN NEURAL NETWORKS BY USING
INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION
FOR TIME SERIES FORCASTING |
| title_sort | model selection in neural networks by using inference of f incremental pca and sic criterion for time series forcasting |
| topic | Statistics |
| url | https://repository.ugm.ac.id/32902/1/1.pdf |
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