References
- Anderson, T. W. (1951). Classification by multivariate analysis, Psychometrika, 16, 31-50 https://doi.org/10.1007/BF02313425
- Anderson, T. W. (1957). Maximum likelihood estimates for a multivariate normal distribution when some observations are missing, Journal of the American Statistical Association, 52, 200-203 https://doi.org/10.2307/2280845
- Anderson, T. W. (1984). An Introduction to Multivariate Statistical Analysis, John Wiley & Sons, New York
- Bohannon, T. R. and Smith, W. B. (1975). ASA Proceedings of Social Statistics Section, 214-218
- Buckland, S. T. (1983). Monte Carlo methods for confidence interval estimation using the bootstrap technique, Bias, 10, 194-212 https://doi.org/10.1080/02664768300000017
- Buckland, S. T. (1984). Monte Carlo confidence intervals, Biometrics, 40, 811-817 https://doi.org/10.2307/2530926
- Buckland, S. T. (1985). Calculation of Monte Carlo confidence intervals, Royal Statistical Society, Algorithm AS214, 297-301
- Chan, L. S. and Dunn, O. J. (1972). The treatment of missing values in discriminant analysis-1, The sampling experiment, Journal of the American Statistical Association, 67, 473-477 https://doi.org/10.2307/2284409
- Chan, L. S. and Dunn, O. J. (1974). A note on the asymptotical aspect of the treatment of missing values in discriminant analysis, Journal of the American Statistical Association, 69, 672-673 https://doi.org/10.2307/2285999
- Chung, H. C. and Han, C. P. (2000). Discriminant analysis when a block of observations is missing, Annals of the Institute of Statistical Mathematics, 52, 544-556 https://doi.org/10.1023/A:1004129706000
- Dempster, A. P., Laird, N. M. and Rubin, R. J. A. (1977). Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B, 39, 302-306
- Diciccio, T. J. and Efron, B. (1996). Bootstrap confidence intervals, Statistical Science, 11, 189-228 https://doi.org/10.1214/ss/1032280214
- DiCiccio, T. J. and Romano, J. P. (1988). A review of bootstrap confidence intervals, Journal of the Royal Statistical Society, Series B, 50, 338-354
- Dorvlo, A. S. S. (1992). An interval estimation of the probability of misclassification, Journal of Mathematical Analysis and Application, 171, 389-394 https://doi.org/10.1016/0022-247X(92)90352-E
- Efron, B. (1982). The jackknife, the bootstrap, and other resampling plans, CBMS-NSF Regional Conference Series in Applied Mathematics, 38. Society for Industrial and Applied Mathematics(SIAM), Philadelphia
- Efron, B. (1987). Better bootstrap confidence intervals, Journal of the American Statistical Association, 82, 171-200 https://doi.org/10.2307/2289144
- Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems, Annals of Eugenics, 7, 179-188 https://doi.org/10.1111/j.1469-1809.1936.tb02137.x
- Hall, p. (1986a). On the bootstrap and confidence intervals, Annals of Statistics, 14, 1431-1452 https://doi.org/10.1214/aos/1176350168
- Hall, P. (1986b). On the number of bootstrap simulations required to construct a confidence interval, Annals of Statistics, 14, 1453-1462 https://doi.org/10.1214/aos/1176350169
- Hinkley, D. V. (1988). Bootstrap methods, Journal of the Royal Statistical Sociey, Series B, 50, 321-337
- Hocking, R. R. and Smith, W. B. (1968). Estimation of parameters in the mutivariate normal distribu-tion with missing observation, Journal of the American Statistical Association, 63, 159-173 https://doi.org/10.2307/2283837
- Johnson, R. A. and Wichern, D. W. (2002). Applied Multivariate Statistical Analysis, Prentice
- Twedt, D. J. and Gill, D. S. (1992). Comparison of algorithm for replacing missing data in discrimi-nant analysis, Communications in Statistics-Theory and Methods, 21, 1567-1578 https://doi.org/10.1080/03610929208830864