Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ping Feng Xu"'
Publikováno v:
PLoS ONE, Vol 18, Iss 1, p e0279918 (2023)
One of the main concerns in multidimensional item response theory (MIRT) is to detect the relationship between observed items and latent traits, which is typically addressed by the exploratory analysis and factor rotation techniques. Recently, an EM-
Externí odkaz:
https://doaj.org/article/887c50f6137745558650cf1795e59a9b
Autor:
Qian-Zhen Zheng, Ping-Feng Xu
Publikováno v:
Journal of the Franklin Institute. 359:9376-9400
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::611fb2d8d123b178e2f79f3112d86e33
https://doi.org/10.1016/j.jfranklin.2022.09.002
https://doi.org/10.1016/j.jfranklin.2022.09.002
Publikováno v:
The British journal of mathematical and statistical psychologyReferences. 75(2)
The aim of latent variable selection in multidimensional item response theory (MIRT) models is to identify latent traits probed by test items of a multidimensional test. In this paper the expectation model selection (EMS) algorithm proposed by Jiang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39e69c4e8170d9f7373bfbd22fe51d12
https://pubmed.ncbi.nlm.nih.gov/34918834
https://pubmed.ncbi.nlm.nih.gov/34918834
Bounds on the average causal effects in randomized trials with noncompliance by covariate adjustment
Autor:
Na Shan, Ping-Feng Xu
Publikováno v:
Biometrical Journal. 58:1311-1318
In randomized trials with noncompliance, causal effects cannot be identified without strong assumptions. Therefore, several authors have considered bounds on the causal effects. Applying an idea of VanderWeele (), Chiba () gave bounds on the average
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fe39dc82e4985816115ee4064ad9735
https://doi.org/10.1002/bimj.201500157
https://doi.org/10.1002/bimj.201500157
Publikováno v:
Computational Statistics & Data Analysis. 95:17-23
The maximum likelihood estimation of hierarchical models for contingency tables is often carried out by the iterative proportional scaling (IPS) procedure. In this paper, we propose local computations of the IPS procedure by partitioning generators.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e3d09bbff8d3168a6566ea67c300483
https://doi.org/10.1016/j.csda.2015.10.009
https://doi.org/10.1016/j.csda.2015.10.009
Publikováno v:
Journal of Computational and Graphical Statistics. 24:205-229
In this article, we propose localized implementations of the iterative proportional scaling (IPS) procedure by the strategy of partitioning cliques for computing maximum likelihood estimations in large Gaussian graphical models. We first divide the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa978af6aadc93743ea38c1b833737af
https://doi.org/10.1080/10618600.2014.900499
https://doi.org/10.1080/10618600.2014.900499
Autor:
Jian-hua Guo, Ping-feng Xu
Publikováno v:
Acta Mathematicae Applicatae Sinica, English Series. 28:571-582
In this paper, we combine Leimer’s algorithm with MCS-M algorithm to decompose graphical models into marginal models on prime blocks. It is shown by experiments that our method has an easier and faster implementation than Leimer’s algorithm.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d0b537172fe5678f4d268e12d50dc53
https://doi.org/10.1007/s10255-012-0170-6
https://doi.org/10.1007/s10255-012-0170-6
Publikováno v:
Computational Statistics & Data Analysis. 55:3135-3147
In this paper, we consider how to recover the structure of a Bayesian network from a moral graph. We present a more accurate characterization of moral edges, based on which a complete subset (i.e., a separator) contained in the neighbor set of one ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5f8656cd2e968d983cf10aee5949735
https://doi.org/10.1016/j.csda.2011.06.017
https://doi.org/10.1016/j.csda.2011.06.017
Publikováno v:
Statistics and Computing. 22:1125-1133
In this paper, we propose an improved iterative proportional scaling procedure for maximum likelihood estimation for multivariate Gaussian graphical models. Our proposed procedure allows us to share computations when adjusting different clique margin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::550941cd8e8b2802f41e05a22d034c16
https://doi.org/10.1007/s11222-011-9286-4
https://doi.org/10.1007/s11222-011-9286-4
Publikováno v:
Journal of Computational and Graphical Statistics. 20:417-431
The maximum likelihood estimation of Gaussian graphical models is often carried out by the iterative proportional scaling (IPS) procedure. In this article, we propose an improvement to the IPS procedure by using local computation and by sharing compu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa6a801f1ee7a1ee78f415f22992851c
https://doi.org/10.1198/jcgs.2010.09044
https://doi.org/10.1198/jcgs.2010.09044