-
1دورية أكاديميةTargeted maximum likelihood estimation for causal inference in survival and competing risks analysis
المؤلفون: Rytgaard, Helene C. W., van der Laan, Mark J.
المصدر: Rytgaard , H C W & van der Laan , M J 2024 , ' Targeted maximum likelihood estimation for causal inference in survival and competing risks analysis ' , Lifetime Data Analysis , vol. 30 , pp. 4–33 . https://doi.org/10.1007/s10985-022-09576-2Test
مصطلحات موضوعية: TMLE, Semiparametric efficiency, Survival analysis, Competing risks, Super learning, Highly adaptive lasso, Causal inference, Average treatment effects, REGULARIZATION PATHS, CUMULATIVE INCIDENCE, ADJUVANT THERAPY, FLUOROURACIL, LEVAMISOLE, OUTCOMES, HAZARDS, TRIALS, MODELS
الإتاحة: https://doi.org/10.1007/s10985-022-09576-2Test
https://curis.ku.dk/portal/da/publications/targeted-maximum-likelihood-estimation-for-causal-inference-in-survival-and-competing-risks-analysisTest(eaf1cf79-6c5e-4f3c-99ce-30cadb26bd9e).html -
2دورية أكاديمية
المؤلفون: Ding, Jie, Li, Jialiang, Han, Yang, McKeague, Ian, Wang, Xiaoguang
المصدر: Ding , J , Li , J , Han , Y , McKeague , I & Wang , X 2023 , ' Fitting additive risk models using auxiliary information ' , Statistics in medicine , vol. 42 , no. 6 , pp. 894-916 . https://doi.org/10.1002/sim.9649Test
مصطلحات موضوعية: adaptive lasso, additive risk model, generalized method of moments, heterogeneity, information synthesis, penalty function, sparse estimation
الإتاحة: https://doi.org/10.1002/sim.9649Test
https://research.manchester.ac.uk/en/publications/633b3ed9-9c37-4efd-a7ed-1a4a8df7ac53Test -
3دورية أكاديمية
المؤلفون: Smeekes, Stephan, Wijler, Etienne
المصدر: Smeekes , S & Wijler , E 2018 , ' Macroeconomic forecasting using penalized regression methods ' , International Journal of Forecasting , vol. 34 , no. 3 , pp. 408-430 . https://doi.org/10.1016/j.ijforecast.2018.01.001Test
مصطلحات موضوعية: Forecasting, Lasso, Factor models, High-dimensional data, Cointegration, DYNAMIC FACTOR MODELS, PRINCIPAL COMPONENT ANALYSIS, APPROXIMATE FACTOR MODELS, TIME-SERIES, ADAPTIVE LASSO, LARGE NUMBER, SELECTION, PREDICTORS, SHRINKAGE, AUTOREGRESSIONS
وصف الملف: application/pdf
الإتاحة: https://doi.org/10.1016/j.ijforecast.2018.01.001Test
https://cris.maastrichtuniversity.nl/en/publications/2c197d0d-0f36-4199-8c4d-4be1c9e86fc9Test
https://cris.maastrichtuniversity.nl/ws/files/53572602/Smeekes_2018_Macroeconomic_forecasting_using_penalized_regression_methods.pdfTest
https://linkinghub.elsevier.com/retrieve/pii/S0169207018300074Test -
4دورية أكاديمية
المؤلفون: Wit, Ernst C.
المصدر: Wit , E C 2018 , ' A penalized inference approach to stochastic block modelling of community structure in the Italian Parliament ' , Journal of the Royal Statistical Society. Series C: Applied Statistics , vol. 67 , no. 2 , pp. 355-369 . https://doi.org/10.1111/rssc.12234Test
مصطلحات موضوعية: Adaptive lasso, Bill cosponsorship, Community structure, Network, Penalized likelihood, Stochastic block model, EXPONENTIAL-FAMILY, ORACLE PROPERTIES, DIRECTED-GRAPHS, BLOCKMODELS, SELECTION, LIKELIHOOD, NETWORKS, LASSO
وصف الملف: application/pdf
الإتاحة: https://doi.org/10.1111/rssc.12234Test
https://hdl.handle.net/11370/949900c1-d2cd-4b2c-ade3-51bc8dba21cfTest
https://research.rug.nl/en/publications/949900c1-d2cd-4b2c-ade3-51bc8dba21cfTest
https://pure.rug.nl/ws/files/54284356/Signorelli_et_al_2018_Journal_of_the_Royal_Statistical_Society_Series_C_Applied_Statistics_.pdfTest -
5دورية أكاديمية
المؤلفون: Van Erp, Sara, Oberski, Daniel L., Mulder, Joris
المصدر: Van Erp , S , Oberski , D L & Mulder , J 2019 , ' Shrinkage priors for Bayesian penalized regression ' , Journal of Mathematical Psychology , vol. 89 , pp. 31-50 . https://doi.org/10.1016/j.jmp.2018.12.004Test
مصطلحات موضوعية: ADAPTIVE LASSO, Bayesian, Empirical Bayes, FREQUENTIST, HORSESHOE, INFORMATION, MODELS, Penalization, REGULARIZATION, Regression, Shrinkage priors, VARIABLE-SELECTION
العلاقة: https://research.tilburguniversity.edu/en/publications/f2d954c3-8100-413e-af40-74c2176d6e4dTest
الإتاحة: https://doi.org/10.1016/j.jmp.2018.12.004Test
https://research.tilburguniversity.edu/en/publications/f2d954c3-8100-413e-af40-74c2176d6e4dTest -
6دورية أكاديمية
المصدر: Kallestrup-Lamb , M , Kock , A B & Kristensen , J T 2016 , ' Lassoing the Determinants of Retirement ' , Econometric Reviews , vol. 35 , no. 8-10 , pp. 1522-1561 . https://doi.org/10.1080/07474938.2015.1092803Test
مصطلحات موضوعية: Adaptive Lasso, High-dimensional data, Lasso, Logistic regression, Oracle property, Register data, Retirement
العلاقة: https://portal.findresearcher.sdu.dk/da/publications/ada8472b-3c16-421b-b06f-cc40b301b79aTest
الإتاحة: https://doi.org/10.1080/07474938.2015.1092803Test
https://portal.findresearcher.sdu.dk/da/publications/ada8472b-3c16-421b-b06f-cc40b301b79aTest