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He, Xuming Lin, Nan 2015-09-28T16:02:42Z 2015-09-28T16:02:42Z 10000-01-01 2003 2003 Imprecisely or incompletely observed data often appear in engineering, epidemiology and economic studies, observations on certain variables may be grouped or measured with errors, which poses challenges to the usual statistical methods. This thesis consists of three studies in this general area. First, we study linear calibration of a crude device to a more accurate one. Second, we use the Markov Chain Monte Carlo (MCMC) method to handle a grouped independent variable in a linear model as motivated by a residential energy study. The third study is concerned with an approximate minimum Hellinger distance estimator (AMHDE) under appropriate grouping of data from a continuous variable. The estimator is shown to be asymptotically normal with good efficiency and robustness. Made available in DSpace on 2015-09-28T16:02:42Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3101906.pdf: 3783407 bytes, checksum: 9a5ac72e90568fa4df7d40e4bf143e57 (MD5) Previous issue date: 2003 Embargo set by: Seth Robbins for item 88677 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 99 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003. http://hdl.handle.net/2142/87396 (MiAaPQ)AAI3101906 eng Statistics Three Statistical Problems With Imprecisely or Incompletely Observed Data text Statistics Statistics University of Illinois at Urbana-Champaign Dissertation Ph.D.