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10.1016/j.jmva.2014.05.008 http://scihub22266oqcxt.onion/10.1016/j.jmva.2014.05.008 C4204219!4204219 !25346552     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\25346552 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Multivar+Anal 2014 ; 130 (ä): 118-133 Nephropedia Template TP {{tp|p=25346552 |t=2014. Specification test for Markov models with measurement errors |pdf=|usr=}}{{25346552 }} gab.com Text Specification test for Markov models with measurement errors JO: J Multivar Anal http://www.kidney.de/pget.php?&tw=1&pmid=25346552 #FOAvip Most existing works on specification testing assume that we have direct observations from the model of interest. We study specification testing for Markov models based on contaminated observations. The evolving model dynamics of the unobservable Markov chain is implicitly coded into the conditional distribution of the observed process. To test whether the underlying Markov chain follows a parametric model, we propose measuring the deviation between nonparametric and parametric estimates of conditional regression functions of the observed process. Specifically, we construct a nonparametric simultaneous confidence band for conditional regression functions and check whether the parametric estimate is contained within the band. Twit Text FOAVip Specification test for Markov models with measurement errors ????J Multivar Anal http://www.kidney.de/pget.php?&tw=1&pmid=25346552 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25346552 #FOAvip English Wikipedia <ref>{{Cite pmid|25346552 }}</ref> Specification test for Markov models with measurement errors #MMPMID25346552 Kim S ; Zhao Z J Multivar Anal 2014[Sep]; 130 (ä): 118-133 PMID25346552 show ga Most existing works on specification testing assume that we have direct observations from the model of interest. We study specification testing for Markov models based on contaminated observations. The evolving model dynamics of the unobservable Markov chain is implicitly coded into the conditional distribution of the observed process. To test whether the underlying Markov chain follows a parametric model, we propose measuring the deviation between nonparametric and parametric estimates of conditional regression functions of the observed process. Specifically, we construct a nonparametric simultaneous confidence band for conditional regression functions and check whether the parametric estimate is contained within the band. äSpecification test for Markov models with measurement errors (epmc).pdf DeepDyve Pubget Overpricing