Sample Selection Model with Bootstrap (BPSSM) Approach: Case Study of the Malaysian Population and Family Survey

Lola, Muhamad Safiih; Alwi, Wan Saliha Wan; Zainuddin, Nurul Hila

doi:10.4236/ojs.2016.65060

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…This method is as a replacement for recalculations of point estimation by often eliminate observations. [ [24]. The feasibility using the bootstrap to generate consistent estimates is stated in [25] study, which also suggests that bootstrap is a useful method to calculate the sampling distribution.…”

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confidence: 95%

Bootstrap Approaches to Autoregressive Model on Exchange Rates Currency

Lola¹,

David²,

Zainuddin³

2016

OJS

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The use of historical data is important in making the predictions, for instance in the exchange rate. However, in the construction of a model, extreme data or dirtiness of data is inevitable. In this study, AR model is used with the exchange rate historical data (January 2007 until December 2007) for USD/MYR and is divided into 1-, 3-and 6-horizontal months respectively. Since the presence of extreme data will affect the accuracy of the results obtained in a prediction. Therefore, to obtain a more accurate prediction results, the bootstrap approach was implemented by hybrid with AR model coins as the Bootstrap Autoregressive model (BAR). The effectiveness of the proposed model is investigated by comparing the existing and the proposed model through the statistical performance methods which are RMSE, MAE and MAD. The comparison involves 1%, 5% and 10% for each horizontal month. The results showed that the BAR model performed better than the AR model in terms of sensitivity to extreme data, the accuracy of forecasting models, efficiency and predictability of the model prediction. In conclusion, bootstrap method can alleviate the sensitivity of the model to the extreme data, thereby improving the accuracy of forecasting model which also have high prediction efficiency and that can increase the predictability of the model.

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confidence: 95%

Bootstrap Approaches to Autoregressive Model on Exchange Rates Currency

Lola¹,

David²,

Zainuddin³

2016

OJS

Self Cite

View full text Add to dashboard Cite

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A Hybrid Neural Network Model to Forecast Arrival Guest in Malaysia

Hila

Shaharudin

et al. 2019

2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)

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Double Bootstrap Control Chart for Monitoring Sukuk Volatility at Bursa Malaysia

et al. 2017

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The bootstrap approach on control limit has provided a solution in solving uncertainty estimation problem in control chart performance. However, the limitation of this standard chart has shown to be less efficient and invalidation at certain magnitude shift, especially the monitored sample data is assumed from skewed family distribution. Thus, in this study, a double bootstrap base-model and its control limit is developed in order to improve the efficiency and decrease the invalidation chart performance. In order to test the performance of proposed model, a simulation study using Average Run Length (ARL) and Type II Error rate were implemented. The result has shown that the proposed chart is sensitive and effective in detecting the shift process for small and medium size of skewed sample data. Also, it has found that the proposed chart shown to has better performance on large magnitude shift. The performance of the proposed model was investigated further using sukuk volatility data at Bursa Malaysia. The result revealed that the double bootstrap control chart is sensitive to small shifts process when it can detect changes in the volatility faster. In other words, it is efficient in monitoring the shifts process. Thus, the proposed model could help the traders in making a new decision, for example, either save/hold for a certain period, sell or buy the sukuk certificate.

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Sample Selection Model with Bootstrap (BPSSM) Approach: Case Study of the Malaysian Population and Family Survey

Cited by 3 publications

References 6 publications

Bootstrap Approaches to Autoregressive Model on Exchange Rates Currency

Bootstrap Approaches to Autoregressive Model on Exchange Rates Currency

A Hybrid Neural Network Model to Forecast Arrival Guest in Malaysia

Double Bootstrap Control Chart for Monitoring Sukuk Volatility at Bursa Malaysia

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