caa a22 4500 475793145 CHVBK 20180406123716.0 cr unu---uuuuu 170329e20000901xx s 000 0 eng 10.1007/s001840000051 doi (NATIONALLICENCE)springer-10.1007/s001840000051 Relevance weighted likelihood for dependent data [Elektronische Daten] [Feifang Hu, William F. Rosenberger, James V. Zidek] Abstract.: The relevance-weighted likelihood function weights individual contributions to the likelihood according to their relevance for the inferential problem of interest. Consistency and asymptotic normality of the weighted maximum likelihood estimator were previously proved for independent sequences of random variables. We extend these results to apply to dependent sequences, and, in so doing, provide a unified approach to a number of diverse problems in dependent data. In particular, we provide a heretofore unknown approach for dealing with heterogeneity in adaptive designs, and unify the smoothing approach that appears in many foundational papers for independent data. Applications are given in clinical trials, psychophysics experiments, time series models, transition models, and nonparametric regression. Springer-Verlag Berlin Heidelberg, 2000 Key words: Adaptive designs nationallicence asymptotic normality nationallicence consistency nationallicence generalized estimating equations nationallicence martingales nationallicence nonparametric regression nationallicence smoothing autoregression model nationallicence urn model nationallicence Hu Feifang Department of Statistics and Applied Probability, National University of Singapore, Singapore 119260 (e-mail: stahuff@stat.nus.sg.edu), SG aut Rosenberger William F. Department of Mathematics and Statistics, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, U.S.A. (e-mail: billr@math.umbc.edu), US aut Zidek James V. Department of Statistics, University of British Columbia, Vancouver, BC V6T 1Z2, Canada (e-mail: jim@stat.ubc.ca), CA aut https://doi.org/10.1007/s001840000051 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s001840000051 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hu Feifang Department of Statistics and Applied Probability, National University of Singapore, Singapore 119260 (e-mail: stahuff@stat.nus.sg.edu), SG aut NATIONALLICENCE 700 1- Rosenberger William F. Department of Mathematics and Statistics, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, U.S.A. (e-mail: billr@math.umbc.edu), US aut NATIONALLICENCE 700 1- Zidek James V. Department of Statistics, University of British Columbia, Vancouver, BC V6T 1Z2, Canada (e-mail: jim@stat.ubc.ca), CA aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer