Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Lu-Hung Chen"'
Autor:
Lu-Hung Chen, 陳律閎
98
Multiparameter likelihood models (MLMs) with multiple covariates have a wide range of applications; however, they encounter the “curse of dimension- ality” problem when the dimension of the covariates is large. We develop a generalized mu
Multiparameter likelihood models (MLMs) with multiple covariates have a wide range of applications; however, they encounter the “curse of dimension- ality” problem when the dimension of the covariates is large. We develop a generalized mu
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/58043974660130747347
Autor:
Ci-Ren Jiang, Wei Chih Cheng, Yuh-Lin Wang, Chi Hung Lin, Lu Hung Chen, Da-Wei Wang, Juen-Kai Wang, Yu Ming Deng, Ruwen Jou
Publikováno v:
Analytical Chemistry. 93:2785-2792
Tuberculosis caused by Mycobacterium tuberculosis complex (MTBC) is one of the major infectious diseases in the world. Identification of MTBC and differential diagnosis of nontuberculous mycobacteria (NTM) species impose challenges because of their t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5b382e720fbef12357943fd48aa1538
https://doi.org/10.1021/acs.analchem.0c03681
https://doi.org/10.1021/acs.analchem.0c03681
Autor:
Hao-An Yang, Shu-Min Tsai, Ming-Lin Chuang, Hong-Wei Yan, Yung-Cheng Yao, Guan-Wei Chen, Lu-Hung Chen
Publikováno v:
ICCE-TW
Fish is rich in high-protein, multi-vitamins, low-calorie, and other nutritional value. It is an indispensable delicacy. How to choose fresh fish is a difficult work. Although experts suggest three observation points for choosing fresh fish: 1. Fish
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92afc61ffb7ed627475235776d50f8d2
https://doi.org/10.1109/icce-tw52618.2021.9602879
https://doi.org/10.1109/icce-tw52618.2021.9602879
Sensible Functional Linear Discriminant Analysis Effectively Discriminates Enhanced Raman Spectra of
Autor:
Wei-Chih, Cheng, Lu-Hung, Chen, Ci-Ren, Jiang, Yu-Ming, Deng, Da-Wei, Wang, Chi-Hung, Lin, Ruwen, Jou, Juen-Kai, Wang, Yuh-Lin, Wang
Publikováno v:
Analytical chemistry. 93(5)
Tuberculosis caused by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::a579e26e8004b631d0bab26a27e7c9d7
https://pubmed.ncbi.nlm.nih.gov/33480698
https://pubmed.ncbi.nlm.nih.gov/33480698
Autor:
Lu-Hung Chen, Ci-Ren Jiang
Publikováno v:
Statistics and Computing. 27:1181-1192
Functional principal component analysis is one of the most commonly employed approaches in functional and longitudinal data analysis and we extend it to analyze functional/longitudinal data observed on a general $d$-dimensional domain. The computatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a89c99caaf542dfccab53972b7b6b66
https://doi.org/10.1007/s11222-016-9679-5
https://doi.org/10.1007/s11222-016-9679-5
Publikováno v:
IEEE BigData
Erasable-itemset mining used in production planning identifies itemsets (or components) that, if removed, would not affect profits. Formally, an itemset is erasable if its gain ratio is equal to or smaller than a given maximum gain-ratio threshold r.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9afe30c1364f3dfbae14ae34178235eb
https://doi.org/10.1109/bigdata.2017.8258125
https://doi.org/10.1109/bigdata.2017.8258125
Autor:
Lu-Hung Chen, Ci-Ren Jiang
Fisher’s linear discriminant analysis (LDA) is extended to both densely recorded functional data and sparsely observed longitudinal data for general c -category classification problems. An efficient approach is proposed to identify the optimal LDA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6aa177da385b81f862a789cf16f9d3ea
http://arxiv.org/abs/1606.03844
http://arxiv.org/abs/1606.03844
Publikováno v:
Journal of the American Statistical Association. 104:1179-1191
Multiparameter likelihood models (MLMs) with multiple covariates have a wide range of applications; however, they encounter the “curse of dimensionality” problem when the dimension of the covariates is large. We develop a generalized multiparamet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab55d16158318920f94bf8cc7de6ac7c
https://doi.org/10.1198/jasa.2009.tm08430
https://doi.org/10.1198/jasa.2009.tm08430
Publikováno v:
Journal of Statistical Planning and Inference. 139:236-245
First, we propose a new method for estimating the conditional variance in heteroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of the local linear and local likelihood estimators. Se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3575e4eea995422903ddbdca31b66a0
https://doi.org/10.1016/j.jspi.2008.04.020
https://doi.org/10.1016/j.jspi.2008.04.020
Publikováno v:
ICPR
Linear discriminant analysis that takes spatial smoothness into account has been developed and widely used in image processing society. However, two questions remain unanswered. First, which is the best way to incorporate the smoothness property of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f194131a883fce563e005b62f0c2347
https://doi.org/10.1109/icpr.2014.738
https://doi.org/10.1109/icpr.2014.738