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A Monte Carlo Comparison of Two Linear Dimension Reduction Matrices for Statistical Discrimination
並列摘要
We compare two linear dimension-reduction methods for statistical discrimination in terms of average probabilities of misclassification in reduced dimensions. Using Monte Carlo simulation we compare the dimension-reduction methods over several different parameter configurations of multivariate normal populations and find that the two methods yield very different results. We also apply the two dimension-reduction methods examined here to data from a study on football helmet design and neck injuries.
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延伸閱讀
- 陳昂佑（2008）。Implementation and Application of Adjoint Function Methodology in Variance Reduction of Monte Carlo Calculation〔博士論文，國立清華大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0016-0903200911353185
- Septier, F., Delignon, Y., Rivenq, A. M., & Garnier, C. (2010). Pilot-Aided Sequential Monte Carlo Estimation of Phase Distortions and Transmitted Symbols in Multicarrier Systems. Journal of Electrical and Computer Engineering, 2010(), 290-294. https://doi.org/10.1155/2010/536057
- Fan, F., Zhang, M., Peng, Z., Chen, J., Su, M., Moghtaderi, B., & Doroodchi, E. (2017). Direct Simulation Monte Carlo Method for Acoustic Agglomeration under Standing Wave Condition. Aerosol and Air Quality Research, 17(4), 1073-1083. https://doi.org/10.4209/aaqr.2016.07.0322
- 黃琬庭（2010）。An evaluation of various pairwise multiple comparison procedures under several distributions by Monte Carlo simulation〔碩士論文，淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2010.00215
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