메뉴 건너뛰기




Volumn 54, Issue 12, 2010, Pages 3336-3347

Frequentist Model Averaging with missing observations

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; DATA HANDLING;

EID: 77955273968     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2009.07.023     Document Type: Article
Times cited : (48)

References (36)
  • 1
    • 78049334254 scopus 로고    scopus 로고
    • Robust model selection in regression via weighted likelihood methodology
    • Agostinelli, C., 2002. Robust model selection in regression via weighted likelihood methodology. Statistics and Probability Letters 64, 583-639.
    • (2002) Statistics and Probability Letters , vol.64 , pp. 583-639
    • Agostinelli, C.1
  • 4
    • 38149109794 scopus 로고    scopus 로고
    • On properties of predictors derived with a two-step bootstrap model averaging approach - A simulation study in the linear regression model
    • Buchholz, A., Holländer, N., Sauerbrei, W., 2008. On properties of predictors derived with a two-step bootstrap model averaging approach - a simulation study in the linear regression model. Computational Statistics and Data Analysis 52, 2778-2793.
    • (2008) Computational Statistics and Data Analysis , vol.52 , pp. 2778-2793
    • Buchholz, A.1    Holländer, N.2    Sauerbrei, W.3
  • 5
    • 0030613470 scopus 로고    scopus 로고
    • Model selection: An integral part of inference
    • Buckland, S.T., Burnham, K.P., Augustin, N.H., 1997. Model selection: An integral part of inference. Biometrics 53, 603-618.
    • (1997) Biometrics , vol.53 , pp. 603-618
    • Buckland, S.T.1    Burnham, K.P.2    Augustin, N.H.3
  • 6
    • 0032536651 scopus 로고    scopus 로고
    • An akaike information criterion for model selection in the presence of incomplete data
    • Cavanaugh, J., Shumway, R., 1998. An akaike information criterion for model selection in the presence of incomplete data. Journal of Statistical Planning and Inference 67, 45-65.
    • (1998) Journal of Statistical Planning and Inference , vol.67 , pp. 45-65
    • Cavanaugh, J.1    Shumway, R.2
  • 7
    • 0041611508 scopus 로고    scopus 로고
    • Nearest neighbor imputation for survey data
    • Chen, J., Shao, J., 2000. Nearest neighbor imputation for survey data. Journal of Official Statistics 16, 113-131.
    • (2000) Journal of Official Statistics , vol.16 , pp. 113-131
    • Chen, J.1    Shao, J.2
  • 8
    • 56049125498 scopus 로고    scopus 로고
    • Variable selection with incomplete covariate data
    • Claeskens, G., Consentiras, F., 2008. Variable selection with incomplete covariate data. Biometrics 64, 1062-1069.
    • (2008) Biometrics , vol.64 , pp. 1062-1069
    • Claeskens, G.1    Consentiras, F.2
  • 10
    • 39649119432 scopus 로고    scopus 로고
    • Minimising average risk in regression models
    • Claeskens, G., Hjort, N.L., 2008. Minimising average risk in regression models. Econometric Theory 24, 493-527.
    • (2008) Econometric Theory , vol.24 , pp. 493-527
    • Claeskens, G.1    Hjort, N.L.2
  • 11
    • 32044449925 scopus 로고
    • Generalized cross-validation as a method for choosing a good ridge parameter
    • Golub, G.H., Heath, M., Wahba, G., 1979. Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics 21, 215-223.
    • (1979) Technometrics , vol.21 , pp. 215-223
    • Golub, G.H.1    Heath, M.2    Wahba, G.3
  • 13
    • 34250303142 scopus 로고    scopus 로고
    • Least squares model averaging
    • Hansen, B.E., 2007. Least squares model averaging. Econometrica 75, 1175-1189.
    • (2007) Econometrica , vol.75 , pp. 1175-1189
    • Hansen, B.E.1
  • 14
    • 53649099464 scopus 로고    scopus 로고
    • Least squares forecast averaging
    • Hansen, B.E., 2008. Least squares forecast averaging. Journal of Econometrics 146, 342-350.
    • (2008) Journal of Econometrics , vol.146 , pp. 342-350
    • Hansen, B.E.1
  • 15
    • 33745947404 scopus 로고    scopus 로고
    • Model selection for incomplete and design based samples
    • Hens, N., Aerts, M.G.M., 2006. Model selection for incomplete and design based samples. Statistics in Medicine 25, 2502-2520.
    • (2006) Statistics in Medicine , vol.25 , pp. 2502-2520
    • Hens, N.1    Aerts, M.G.M.2
  • 17
    • 33846098896 scopus 로고    scopus 로고
    • Focussed information criteria and model averaging for Cox's hazard regression model
    • Hjort, N.L, Claeskens, G., 2006. Focussed information criteria and model averaging for Cox's hazard regression model. Journal of the American Statistical Association 101, 1449-1464.
    • (2006) Journal of the American Statistical Association , vol.101 , pp. 1449-1464
    • Hjort, N.L.1    Claeskens, G.2
  • 20
    • 0035285349 scopus 로고    scopus 로고
    • Analyzing incomplete political science data: An alternative algorithm for multiple imputation
    • King, G., Honaker, J., Joseph, A., Scheve, K., 2001. Analyzing incomplete political science data: An alternative algorithm for multiple imputation. American Political Science Review 95, 49-69.
    • (2001) American Political Science Review , vol.95 , pp. 49-69
    • King, G.1    Honaker, J.2    Joseph, A.3    Scheve, K.4
  • 21
    • 0037706986 scopus 로고    scopus 로고
    • The finite sample distribution of post-model-selection estimators and uniform versus non-uniform approximations
    • Leeb, H., Pötscher, B.M., 2003. The finite sample distribution of post-model-selection estimators and uniform versus non-uniform approximations. Econometric Theory 19, 100-142.
    • (2003) Econometric Theory , vol.19 , pp. 100-142
    • Leeb, H.1    Pötscher, B.M.2
  • 22
    • 15744376883 scopus 로고    scopus 로고
    • Model selection and inference: Facts and fiction
    • Leeb, H., Pötscher, B.M., 2005. Model selection and inference: Facts and fiction. Econometric Theory 21, 21-59.
    • (2005) Econometric Theory , vol.21 , pp. 21-59
    • Leeb, H.1    Pötscher, B.M.2
  • 23
    • 33847415033 scopus 로고    scopus 로고
    • Can one estimate the conditional distribution of post-model-selection estimators
    • Leeb, H., Pötscher, B.M., 2006. Can one estimate the conditional distribution of post-model-selection estimators. Annals of Statistics 34, 2554-2591.
    • (2006) Annals of Statistics , vol.34 , pp. 2554-2591
    • Leeb, H.1    Pötscher, B.M.2
  • 24
    • 39649113562 scopus 로고    scopus 로고
    • Can one estimate the unconditional distribution of post-model-selection estimators
    • Leeb, H., Pötscher, B.M., 2008. Can one estimate the unconditional distribution of post-model-selection estimators. Econometric Theory 24, 338-376.
    • (2008) Econometric Theory , vol.24 , pp. 338-376
    • Leeb, H.1    Pötscher, B.M.2
  • 25
    • 33746478298 scopus 로고    scopus 로고
    • Information theory and mixing least squares regressions
    • Leung, G., Barron, A.R., 2006. Information theory and mixing least squares regressions. IEEE Transactions on Information Theory 52, 3396-3410.
    • (2006) IEEE Transactions on Information Theory , vol.52 , pp. 3396-3410
    • Leung, G.1    Barron, A.R.2
  • 27
    • 24344443708 scopus 로고    scopus 로고
    • Missing at random, likelihood ignorability and model completeness
    • Lu, G., Copas, J.B., 2004. Missing at random, likelihood ignorability and model completeness. Annals of Statistics 32, 754-765.
    • (2004) Annals of Statistics , vol.32 , pp. 754-765
    • Lu, G.1    Copas, J.B.2
  • 28
    • 0031485477 scopus 로고    scopus 로고
    • Robustness aspects of model choice
    • Ronchetti, E., 1997. Robustness aspects of model choice. Statistica Sinica 7, 327-338.
    • (1997) Statistica Sinica , vol.7 , pp. 327-338
    • Ronchetti, E.1
  • 30
    • 0041724163 scopus 로고    scopus 로고
    • Coaching variables for regression and classification
    • Tibsharani, R., Hinton, G., 1998. Coaching variables for regression and classification. Statistics and Computing 8, 25-33.
    • (1998) Statistics and Computing , vol.8 , pp. 25-33
    • Tibsharani, R.1    Hinton, G.2
  • 32
    • 35349017857 scopus 로고    scopus 로고
    • Enjoy the joy of copulas: With package copula
    • Yan, J., 2007. Enjoy the joy of copulas: With package copula. Journal of Statistical Software 21, 1-21.
    • (2007) Journal of Statistical Software , vol.21 , pp. 1-21
    • Yan, J.1
  • 34
    • 0141573227 scopus 로고    scopus 로고
    • Regression with multiple candidate models: Selecting or mixing
    • Yang, Y., 2003. Regression with multiple candidate models: Selecting or mixing. Statistica Sinica 13, 783-809.
    • (2003) Statistica Sinica , vol.13 , pp. 783-809
    • Yang, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.