Matches in SemOpenAlex for { <https://semopenalex.org/work/W3206719683> ?p ?o ?g. }
- W3206719683 endingPage "578" @default.
- W3206719683 startingPage "557" @default.
- W3206719683 abstract "Markov chain Monte Carlo (MCMC) is an essential set of tools for estimating features of probability distributions commonly encountered in modern applications. For MCMC simulation to produce reliable outcomes, it needs to generate observations representative of the target distribution, and it must be long enough so that the errors of Monte Carlo estimates are small. We review methods for assessing the reliability of the simulation effort, with an emphasis on those most useful in practically relevant settings. Both strengths and weaknesses of these methods are discussed. The methods are illustrated in several examples and in a detailed case study. Expected final online publication date for the Annual Review of Statistics, Volume 9 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates." @default.
- W3206719683 created "2021-10-25" @default.
- W3206719683 creator A5003702810 @default.
- W3206719683 creator A5075145472 @default.
- W3206719683 date "2022-03-07" @default.
- W3206719683 modified "2023-09-25" @default.
- W3206719683 title "Markov Chain Monte Carlo in Practice" @default.
- W3206719683 cites W1547388036 @default.
- W3206719683 cites W1558800859 @default.
- W3206719683 cites W1648907168 @default.
- W3206719683 cites W1963816561 @default.
- W3206719683 cites W1967974027 @default.
- W3206719683 cites W1970956379 @default.
- W3206719683 cites W1973594349 @default.
- W3206719683 cites W1979606171 @default.
- W3206719683 cites W1982508956 @default.
- W3206719683 cites W1982652137 @default.
- W3206719683 cites W1986613495 @default.
- W3206719683 cites W1988251813 @default.
- W3206719683 cites W1990979853 @default.
- W3206719683 cites W1998325101 @default.
- W3206719683 cites W2008703230 @default.
- W3206719683 cites W2017488093 @default.
- W3206719683 cites W2017874618 @default.
- W3206719683 cites W2030911724 @default.
- W3206719683 cites W2032679978 @default.
- W3206719683 cites W2033057584 @default.
- W3206719683 cites W2033190522 @default.
- W3206719683 cites W2033297007 @default.
- W3206719683 cites W2037823872 @default.
- W3206719683 cites W2041355784 @default.
- W3206719683 cites W2042451342 @default.
- W3206719683 cites W2043694962 @default.
- W3206719683 cites W2046338450 @default.
- W3206719683 cites W2047323186 @default.
- W3206719683 cites W2048971218 @default.
- W3206719683 cites W2060618829 @default.
- W3206719683 cites W2077810240 @default.
- W3206719683 cites W2079434032 @default.
- W3206719683 cites W2082856185 @default.
- W3206719683 cites W2083875149 @default.
- W3206719683 cites W2091512600 @default.
- W3206719683 cites W2095213998 @default.
- W3206719683 cites W2096020040 @default.
- W3206719683 cites W2104863866 @default.
- W3206719683 cites W2106606323 @default.
- W3206719683 cites W2108446661 @default.
- W3206719683 cites W2114005321 @default.
- W3206719683 cites W2120984640 @default.
- W3206719683 cites W2122337269 @default.
- W3206719683 cites W2123736748 @default.
- W3206719683 cites W2127855947 @default.
- W3206719683 cites W2129369039 @default.
- W3206719683 cites W2131858666 @default.
- W3206719683 cites W2136796925 @default.
- W3206719683 cites W2142623799 @default.
- W3206719683 cites W2146764432 @default.
- W3206719683 cites W2148534890 @default.
- W3206719683 cites W2162898443 @default.
- W3206719683 cites W2585461899 @default.
- W3206719683 cites W2592172378 @default.
- W3206719683 cites W2621576843 @default.
- W3206719683 cites W2798428389 @default.
- W3206719683 cites W2889874374 @default.
- W3206719683 cites W2941876699 @default.
- W3206719683 cites W2962777160 @default.
- W3206719683 cites W2962868501 @default.
- W3206719683 cites W2963133138 @default.
- W3206719683 cites W2963254535 @default.
- W3206719683 cites W2963366756 @default.
- W3206719683 cites W2963646841 @default.
- W3206719683 cites W2963937909 @default.
- W3206719683 cites W2972588190 @default.
- W3206719683 cites W2989757660 @default.
- W3206719683 cites W3017508631 @default.
- W3206719683 cites W3022264239 @default.
- W3206719683 cites W3086998293 @default.
- W3206719683 cites W3099871107 @default.
- W3206719683 cites W3100144410 @default.
- W3206719683 cites W3100410719 @default.
- W3206719683 cites W3102299550 @default.
- W3206719683 cites W3102450852 @default.
- W3206719683 cites W3111797293 @default.
- W3206719683 cites W3119740089 @default.
- W3206719683 cites W3124264335 @default.
- W3206719683 cites W3201118272 @default.
- W3206719683 cites W3204992131 @default.
- W3206719683 cites W3207360720 @default.
- W3206719683 cites W4205537960 @default.
- W3206719683 cites W4205696233 @default.
- W3206719683 cites W4233555857 @default.
- W3206719683 cites W4248753860 @default.
- W3206719683 cites W4249731213 @default.
- W3206719683 cites W4250059046 @default.
- W3206719683 cites W4302617909 @default.
- W3206719683 cites W621546036 @default.
- W3206719683 cites W636647991 @default.
- W3206719683 doi "https://doi.org/10.1146/annurev-statistics-040220-090158" @default.