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Volumn 4, Issue 3, 2010, Pages 1579-1601

Sparse logistic principal components analysis for binary data

Author keywords

Binary data; Dimension reduction; LASSO; MM algorithm; PCA; Regularization; Sparsity

Indexed keywords


EID: 80051959023     PISSN: 19326157     EISSN: 19417330     Source Type: Journal    
DOI: 10.1214/10-AOAS327     Document Type: Article
Times cited : (88)

References (27)
  • 1
    • 0033098944 scopus 로고    scopus 로고
    • The lower bound method in probit regression
    • Böhning, D. (1999). The lower bound method in probit regression. Comput. Statist. Data Anal. 30 13-17.
    • (1999) Comput. Statist. Data Anal , vol.30 , pp. 13-17
    • Böhning, D.1
  • 2
    • 0032997217 scopus 로고    scopus 로고
    • Review: The essence of SNPs
    • Brookes, A. J. (1999). Review: The essence of SNPs. Gene 234 177-186.
    • (1999) Gene , vol.234 , pp. 177-186
    • Brookes, A.J.1
  • 3
    • 84899014910 scopus 로고    scopus 로고
    • A generalization of principal component analysis to the exponential family
    • In, (T. G. Dietterich, S. Becker and Z. Ghahramani, eds.), MIT Press, Cambridge, MA
    • Collins, M., Dasgupta, S. and Schapire, R. E. (2002). A generalization of principal component analysis to the exponential family. In Advanced in Neural Information Processing System (T. G. Dietterich, S. Becker and Z. Ghahramani, eds.) 14 617-642. MIT Press, Cambridge, MA.
    • (2002) Advanced in Neural Information Processing System , vol.14 , pp. 617-642
    • Collins, M.1    Dasgupta, S.2    Schapire, R.E.3
  • 4
    • 24644473091 scopus 로고    scopus 로고
    • Principal component analysis of binary data by iterated singular value decomposition
    • de Leeuw, J. (2006). Principal component analysis of binary data by iterated singular value decomposition. Comput. Statist. Data Anal. 50 21-39.
    • (2006) Comput. Statist. Data Anal , vol.50 , pp. 21-39
    • de Leeuw, J.1
  • 5
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm (with discussion)
    • Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm (with discussion). J. Roy. Statist. Soc. Ser. B 39 1-38.
    • (1977) J. Roy. Statist. Soc. Ser. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 6
    • 0029075560 scopus 로고
    • The transmission/disequilibrium test: History, subdivision, and admixture
    • Ewens, W. J. and Spielman, R. S. (1995). The transmission/disequilibrium test: History, subdivision, and admixture. The American Journal of Human Genetics 57 455-464.
    • (1995) The American Journal of Human Genetics , vol.57 , pp. 455-464
    • Ewens, W.J.1    Spielman, R.S.2
  • 8
    • 10044280273 scopus 로고    scopus 로고
    • Detect and adjust for population stratification in population-based association study using genomic control markers: An application of Affymetrix Genechip® Human Mapping 10K array
    • Hao, K., Li, C., Rosenow, C. and Wong, W. H. (2004). Detect and adjust for population stratification in population-based association study using genomic control markers: An application of Affymetrix Genechip® Human Mapping 10K array. European Journal of Human Genetics 12 1001-1006.
    • (2004) European Journal of Human Genetics , vol.12 , pp. 1001-1006
    • Hao, K.1    Li, C.2    Rosenow, C.3    Wong, W.H.4
  • 9
    • 58149421595 scopus 로고
    • Analysis of a complex of statistical variables into principal components
    • Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology 24 417-441.
    • (1933) Journal of Educational Psychology , vol.24 , pp. 417-441
    • Hotelling, H.1
  • 10
    • 1342332031 scopus 로고    scopus 로고
    • A tutorial on MM algorithms
    • Hunter, D. R. and Lange, K. (2004). A tutorial on MM algorithms. Amer. Statist. 58 30-37.
    • (2004) Amer. Statist , vol.58 , pp. 30-37
    • Hunter, D.R.1    Lange, K.2
  • 11
    • 26444617168 scopus 로고    scopus 로고
    • Variable selection using MM algorithms
    • Hunter, D. R. and Li, R. (2005). Variable selection using MM algorithms. Ann. Statist. 33 1617-1642.
    • (2005) Ann. Statist , vol.33 , pp. 1617-1642
    • Hunter, D.R.1    Li, R.2
  • 12
    • 0042685161 scopus 로고    scopus 로고
    • Bayesian parameter estimation via variational methods
    • Jaakkola, T. S. and Jordan, M. I. (2000). Bayesian parameter estimation via variational methods. Statist. Comput. 10 25-37.
    • (2000) Statist. Comput , vol.10 , pp. 25-37
    • Jaakkola, T.S.1    Jordan, M.I.2
  • 14
    • 0141941674 scopus 로고    scopus 로고
    • A modified principal component technique based on the LASSO
    • Jolliffe, I. T., Trendafilov, M. and Uddine, M. (2003). A modified principal component technique based on the LASSO. J. Comput. Graph. Statist. 12 531-547.
    • (2003) J. Comput. Graph. Statist , vol.12 , pp. 531-547
    • Jolliffe, I.T.1    Trendafilov, M.2    Uddine, M.3
  • 15
    • 0030021312 scopus 로고    scopus 로고
    • Increasing the information content of STS-based genome maps: Identifying polymorphisms in mapped STSs
    • Kwok, P. Y., Deng, Q., Zakeri, H., Taylor, S. L. and Nickerson, D. A. (1996). Increasing the information content of STS-based genome maps: Identifying polymorphisms in mapped STSs. Genomics 31 123-126.
    • (1996) Genomics , vol.31 , pp. 123-126
    • Kwok, P.Y.1    Deng, Q.2    Zakeri, H.3    Taylor, S.L.4    Nickerson, D.A.5
  • 16
    • 77950023906 scopus 로고    scopus 로고
    • Optimization transfer using surrogate objective functions (with discussion)
    • Lange, K., Hunter, D. R. and Yang, I. (2000). Optimization transfer using surrogate objective functions (with discussion). J. Comput. Graph. Statist. 9 1-20.
    • (2000) J. Comput. Graph. Statist , vol.9 , pp. 1-20
    • Lange, K.1    Hunter, D.R.2    Yang, I.3
  • 18
    • 55449095941 scopus 로고    scopus 로고
    • Statistical advances and challenges for analyzing correlated high dimensional SNP data in genomic study for complex diseases
    • Liang, Y. and Kelemen, A. (2008). Statistical advances and challenges for analyzing correlated high dimensional SNP data in genomic study for complex diseases. Stat. Surv. 2 43-60.
    • (2008) Stat. Surv , vol.2 , pp. 43-60
    • Liang, Y.1    Kelemen, A.2
  • 23
    • 43049086717 scopus 로고    scopus 로고
    • Sparse principal component analysis via regularized low rank matrix approximation
    • Shen, H. and Huang, J. Z. (2008). Sparse principal component analysis via regularized low rank matrix approximation. J. Multivariate Anal. 99 1015-1034.
    • (2008) J. Multivariate Anal , vol.99 , pp. 1015-1034
    • Shen, H.1    Huang, J.Z.2
  • 24
    • 79959524146 scopus 로고    scopus 로고
    • A haplotype map of the human genome
    • The International HapMap Consortium
    • The International HapMap Consortium (2005). A haplotype map of the human genome. Nature 437 1299-1320.
    • (2005) Nature , vol.437 , pp. 1299-1320
  • 25
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani, R. J. (1996). Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B 58 267-288.
    • (1996) J. Roy. Statist. Soc. Ser. B , vol.58 , pp. 267-288
    • Tibshirani, R.J.1
  • 27
    • 34548536008 scopus 로고    scopus 로고
    • On the "Degrees of Freedom" of the LASSO
    • Zou, H., Hastie, T. J. and Tibshirani, R. J. (2007). On the "Degrees of Freedom" of the LASSO. Ann. Statist. 35 2173-2192.
    • (2007) Ann. Statist , vol.35 , pp. 2173-2192
    • Zou, H.1    Hastie, T.J.2    Tibshirani, R.J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.