Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Guangbao Guo"'
Autor:
Di Chang, Guangbao Guo
Publikováno v:
SoftwareX, Vol 28, Iss , Pp 101909- (2024)
The goal of the Length and Information Optimization Criterion (LIC) is to handle datasets containing redundant information, identify and select the most informative subsets, and ensure that a large portion of the information from the dataset is retai
Externí odkaz:
https://doaj.org/article/d08afc077b8248feb2f6ac25e5ab99fe
Autor:
Guangbao Guo
Publikováno v:
International Journal of Financial Studies, Vol 6, Iss 1, p 26 (2018)
This paper gives a review of numerical methods for solving the BSDEs, especially, finite difference methods. For numerical methods of finite difference, we should divide them into three branches. Distributed method (or parallel method) should now bec
Externí odkaz:
https://doaj.org/article/9a77632cbd234715ae5d757c00c875c1
Autor:
Yu Li1 marlboro0608@163.com, Guangbao Guo2 ggb11111111@163.com
Publikováno v:
IAENG International Journal of Applied Mathematics. Feb2024, Vol. 54 Issue 2, p205-211. 7p.
Autor:
Yaping Li1 lyplyplypsdlg@163.com, Guangbao Guo1 ggb11111111@163.com
Publikováno v:
Engineering Letters. Jan2024, Vol. 32 Issue 1, p72-76. 5p.
Autor:
Limin Song1 songsongsonglm@163.com, Guangbao Guo2 ggb11111111@163.com
Publikováno v:
IAENG International Journal of Applied Mathematics. Jan2024, Vol. 54 Issue 1, p77-81. 5p.
Publikováno v:
Computational Statistics. 38:1095-1116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a02f5136e9833de0e7144ee2c07ee51b
https://doi.org/10.1007/s00180-022-01270-z
https://doi.org/10.1007/s00180-022-01270-z
Autor:
Guangbao Guo1 ggb11111111@163.com, Weidong Zhao2 wdzhao@sdu.edu.cn
Publikováno v:
Journal of Computational Mathematics. 2021, Vol. 39 Issue 4, p515-532. 18p.
Publikováno v:
Communications in Statistics - Simulation and Computation. :1-17
Data sets with missing values bring great challenges to k-means clustering (KMC). At present, most studies focus on KMC data with low missing ratio while few studies on KMC data with high missing ratio. The current imputation methods have the followi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::942a7919571c225467c591ee851d38b9
https://doi.org/10.1080/03610918.2022.2091779
https://doi.org/10.1080/03610918.2022.2091779
Autor:
Guangbao Guo
Publikováno v:
J Appl Stat
It is a major research topic of limited generalized linear models, namely, generalized linear models with limited dependent variables. The models are developed in many research fields. However, quasi-likelihood estimation of the models is an unresolv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4014c966d09cb59175ea6dfc3943a604
https://pubmed.ncbi.nlm.nih.gov/35706991
https://pubmed.ncbi.nlm.nih.gov/35706991
Autor:
Guangbao Guo
Publikováno v:
Statistics. 54:909-925
This article utilizes bootstrap quasi-likelihood (QL) to model sparse functional data. The proposed method combines parallel block bootstrap and QL to fit the functional data. The parameter space i...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::705517d742b38351591dd835d10fb72b
https://doi.org/10.1080/02331888.2020.1823979
https://doi.org/10.1080/02331888.2020.1823979