English | 繁體

Search in the results

UM

Browse/Search Results:  1-10 of 51 Help

Selected(0)Clear Items/Page:    Sort:
Monte Carlo confidence intervals for the indirect effect with missing data Journal article
Pesigan, Ivan Jacob Agaloos, Cheung, Shu Fai. Monte Carlo confidence intervals for the indirect effect with missing data[J]. Behavior Research Methods, 2024, 56(3), 1678-1696.
Authors:  Pesigan, Ivan Jacob Agaloos;  Cheung, Shu Fai
Favorite | TC[WOS]:2 TC[Scopus]:3  IF:4.6/7.2 | Submit date：2024/02/23
Monte Carlo Method  Nonparametric Bootstrap  Indirect Effect  Mediation  Missing Completely At Random  Missing At Random  Full-information Maximum Likelihood  Multiple Imputation  
Fractional gaussian noise: Spectral density and estimation methods Journal article
Shi, Shuping, Yu, Jun, Zhang, Chen. Fractional gaussian noise: Spectral density and estimation methods[J]. Journal of Time Series Analysis, 2024.
Authors:  Shi, Shuping;  Yu, Jun;  Zhang, Chen
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.2/1.4 | Submit date：2024/06/03
Change-of-frequency  Fractional Brownian Motion  Fractional Gaussian Noise  Maximum Likelihood  Realised Volatility  Semi-parametric Method  Whittle Likelihood  
To go or not to go? Exhibition attendees’ risk perception of COVID-19: Evidence from three Asian regions Journal article
Chan,Zi Xuan, Ye,Huiyue, Li,Junhua, Wei,Lexi Dan. To go or not to go? Exhibition attendees’ risk perception of COVID-19: Evidence from three Asian regions[J]. Journal of Convention and Event Tourism, 2023, 24(4), 318-340.
Authors:  Chan,Zi Xuan;  Ye,Huiyue;  Li,Junhua;  Wei,Lexi Dan
Favorite | TC[WOS]:1 TC[Scopus]:2  IF:1.7/1.9 | Submit date：2023/08/03
Covid-19  Elaboration Likelihood Model (Elm)  Exhibition Industry  Risk Perception  Travel Behavior  
Denoising Noisy Neural Networks: A Bayesian Approach with Compensation Journal article
Shao,Yulin, Liew,Soung Chang, Gunduz,Deniz. Denoising Noisy Neural Networks: A Bayesian Approach with Compensation[J]. IEEE Transactions on Signal Processing, 2023, 71, 2460 - 2474.
Authors:  Shao,Yulin;  Liew,Soung Chang;  Gunduz,Deniz
Favorite | TC[WOS]:2 TC[Scopus]:4  IF:4.6/5.2 | Submit date：2023/08/03
Denoiser  Estimation  Federated Edge Learning  Maximum Likelihood Estimation  Neural Networks  Noise Measurement  Noise Reduction  Noisy Neural Network  Training  Wireless Communication  Wireless Transmission Of Neural Networks  
semlbci: An R package for Forming Likelihood-Based Confidence Intervals for Parameter Estimates, Correlations, Indirect Effects, and Other Derived Parameters Journal article
Cheung,Shu Fai, Pesigan,Ivan Jacob Agaloos. semlbci: An R package for Forming Likelihood-Based Confidence Intervals for Parameter Estimates, Correlations, Indirect Effects, and Other Derived Parameters[J]. Structural Equation Modeling, 2023, 30(6), 985 - 999.
Authors:  Cheung,Shu Fai;  Pesigan,Ivan Jacob Agaloos
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:2.5/5.9 | Submit date：2023/08/03
Confidence Interval  Likelihood-based Confidence Interval  Robust Method  Structural Equation Modeling  
Self-Weighted Quasi-Maximum Likelihood Estimators for a Class of MA-GARCH Model Journal article
Xie, Danni, Liang, Xin, Liang, Ruilin. Self-Weighted Quasi-Maximum Likelihood Estimators for a Class of MA-GARCH Model[J]. Symmetry, 2022, 14(8), 1723.
Authors:  Xie, Danni;  Liang, Xin;  Liang, Ruilin
Favorite | TC[Scopus]:0  IF:2.2/2.3 | Submit date：2023/01/30
a Class Of Ma-garch Model  Asymptotic Normatity  The Consistency  The Self-weighted Quasi-maximum Likelihood Estimation  
Graph-based sparse bayesian broad learning system for semi-supervised learning Journal article
Xu, Lili, Philip Chen, C. L., Han, Ruizhi. Graph-based sparse bayesian broad learning system for semi-supervised learning[J]. INFORMATION SCIENCES, 2022, 597, 193-210.
Authors:  Xu, Lili;  Philip Chen, C. L.;  Han, Ruizhi
Favorite | TC[WOS]:13 TC[Scopus]:13  IF:0/0 | Submit date：2022/05/13
Classification  Fast Marginal Likelihood Maximization  Graph-based Model  Manifold Regularization  Semi-supervised Learning  Sparse Bayesian Broad Learning System  
Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions Journal article
Cai, Tianji, Xia, Yiwei, Zhou, Yisu. Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions[J]. Sociological Methods & Research, 2021, 50(1), 365-400.
Authors:  Cai, Tianji;  Xia, Yiwei;  Zhou, Yisu
Adobe PDF | Favorite | TC[WOS]:11 TC[Scopus]:13  IF:6.5/6.0 | Submit date：2019/08/07
Multiple Data Inflations  Generalized Inflated Discrete Models  Maximum Likelihood Estimator  Probabilities Of Inflation  Monte Carlo Experiments  
Forensic Analysis of JPEG-Domain Enhanced Images via Coefficient Likelihood Modeling Journal article
Yang, Jianquan, Zhu, Guopu, Luo, Yao, Kwong, Sam, Zhang, Xinpeng, Zhou, Yicong. Forensic Analysis of JPEG-Domain Enhanced Images via Coefficient Likelihood Modeling[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2021, 32(3), 1006-1019.
Authors:  Yang, Jianquan;  Zhu, Guopu;  Luo, Yao;  Kwong, Sam;  Zhang, Xinpeng; et al.
Favorite | TC[WOS]:6 TC[Scopus]:7  IF:8.3/7.1 | Submit date：2022/03/28
Coefficient Periodicity Analysis  Image Forensics  Jpeg-domain Enhancement  Maximum Likelihood Estimation  Quantization Step Estimation  
Empirical likelihood ratio under infinite covariance matrix of the random vectors Journal article
Cheng,Conghua, Liu,Zhi. Empirical likelihood ratio under infinite covariance matrix of the random vectors[J]. Communications in Statistics - Theory and Methods, 2021, 50(18), 4300-4307.
Authors:  Cheng,Conghua;  Liu,Zhi
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.6/0.8 | Submit date：2021/03/11
Confidence Region  Empirical Likelihood  Infinite Covariance Matrix  Domain Of Attraction Of Normal Law