Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Hea-Jung Kim"'
Autor:
Hea-Jung Kim
Publikováno v:
Entropy, Vol 17, Iss 9, Pp 6481-6502 (2015)
In the application of discriminant analysis, a situation sometimes arises where individual measurements are screened by a multidimensional screening scheme. For this situation, a discriminant analysis with screened populations is considered from a Ba
Externí odkaz:
https://doaj.org/article/63b91a69025249009e71a410f8cd03a2
Publikováno v:
Entropy, Vol 20, Iss 4, p 262 (2018)
In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt) process regression model that assumes a MaxEnt prior distri
Externí odkaz:
https://doaj.org/article/a2cb99ff5e1245ceb73a89abb3cd46d2
Autor:
Hea-Jung Kim
Publikováno v:
Entropy, Vol 19, Iss 6, p 274 (2017)
This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing fa
Externí odkaz:
https://doaj.org/article/01ed742a1c6f4e11a8d949c25f679341
Autor:
Hea-Jung Kim
Publikováno v:
The Scientific World Journal, Vol 2014 (2014)
This paper considers a hierarchical screened Gaussian model (HSGM) for Bayesian inference of normal models when an interval constraint in the mean parameter space needs to be incorporated in the modeling but when such a restriction is uncertain. An o
Externí odkaz:
https://doaj.org/article/1e360d422c0b4fd0ae6d96bc1453bd05
Autor:
Hea-Jung Kim
Publikováno v:
Entropy, Vol 18, Iss 5, p 188 (2016)
This paper proposes a two-stage maximum entropy prior to elicit uncertainty regarding a multivariate interval constraint of the location parameter of a scale mixture of normal model. Using Shannon’s entropy, this study demonstrates how the prior, o
Externí odkaz:
https://doaj.org/article/f21b9465551a447facb1901eb45659c3
Publikováno v:
Statistics. 53:1082-1111
In regression analysis, a sample selection scheme often applies to the response variable, which results in missing not at random observations on the variable. In this case, a regression analysis us...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a08187253bb3e97159eae9f7f2c3455
https://doi.org/10.1080/02331888.2019.1624964
https://doi.org/10.1080/02331888.2019.1624964
Autor:
Hea-Jung Kim
Publikováno v:
Journal of Multivariate Analysis. 164:65-82
This paper introduces a class of scale mixtures of normal selection factor (SMNSF) analysis models which are robust against departures from normality and designed to correct sample-selection bias. Various properties of this class of models are establ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de6d04384df6c288d279ad4ada9f08da
https://doi.org/10.1016/j.jmva.2017.11.003
https://doi.org/10.1016/j.jmva.2017.11.003
Autor:
Hea-Jung Kim, Hyoung-Moon Kim
Publikováno v:
Journal of the Korean Statistical Society. 45:422-438
In linear regression, a multivariate sample-selection scheme often applies to the dependent variable, which results in missing observations on the variable. This induces the sample-selection bias, i.e. a standard regression analysis using only the se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c01d7557d70bebfcea1a67ebce2ee0b2
https://doi.org/10.1016/j.jkss.2016.01.003
https://doi.org/10.1016/j.jkss.2016.01.003
Publikováno v:
Journal of Applied Statistics. 43:2751-2771
This paper provides a Bayesian estimation procedure for monotone regression models incorporating the monotone trend constraint subject to uncertainty. For monotone regression modeling with stochastic restrictions, we propose a Bayesian Bernstein poly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b8c309c98fc9e236ba88b404efd1fb6
https://doi.org/10.1080/02664763.2016.1143456
https://doi.org/10.1080/02664763.2016.1143456
Publikováno v:
Journal of Multivariate Analysis. 144:110-128
Factor analysis with uncertain functional constraints about factor loading matrix is considered from a Bayesian viewpoint, in which the uncertain prior information is incorporated in the analysis. We propose a hierarchical screened scale mixture of n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a9e5e306394b1c162bc1e33df517d08
https://doi.org/10.1016/j.jmva.2015.11.006
https://doi.org/10.1016/j.jmva.2015.11.006