Nonlinear structural equation models for network topology inference

2016 Annual Conference on Information Science and Systems (CISS) ◽

10.1109/ciss.2016.7460495 ◽

2016 ◽

Author(s):

Yanning Shen ◽

Brian Baingana ◽

Georgios B. Giannakis

Keyword(s):

Network Topology ◽

Structural Equation ◽

Structural Equation Models ◽

Topology Inference ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Network topology inference via elastic net structural equation models

2017 25th European Signal Processing Conference (EUSIPCO) ◽

10.23919/eusipco.2017.8081186 ◽

2017 ◽

Author(s):

Panagiotis A. Traganitis ◽

Yanning Shen ◽

Georgios B. Giannakis

Keyword(s):

Network Topology ◽

Structural Equation ◽

Structural Equation Models ◽

Elastic Net ◽

Topology Inference

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Maximum likelihood estimation of nonlinear structural equation models

Psychometrika ◽

10.1007/bf02294842 ◽

2002 ◽

Vol 67 (2) ◽

pp. 189-210 ◽

Author(s):

Sik-Yum Lee ◽

Hong-Tu Zhu

Keyword(s):

Maximum Likelihood ◽

Maximum Likelihood Estimation ◽

Structural Equation ◽

Structural Equation Models ◽

Likelihood Estimation ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Estimation of nonlinear structural equation models with dichotomous indicator variables: a Monte Carlo comparison of methods

International Journal of Quantitative Research in Education ◽

10.1504/ijqre.2020.106565 ◽

2020 ◽

Vol 5 (1) ◽

pp. 39

Author(s):

W. Holmes Finch

Keyword(s):

Monte Carlo ◽

Structural Equation ◽

Structural Equation Models ◽

Comparison Of Methods ◽

Nonlinear Structural ◽

Indicator Variables ◽

Nonlinear Structural Equation ◽

Dichotomous Indicator

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Assessing local influence for nonlinear structural equation models with ignorable missing data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2004.11.012 ◽

2006 ◽

Vol 50 (5) ◽

pp. 1356-1377 ◽

Author(s):

Sik-Yum Lee ◽

Bin Lu ◽

Xin-Yuan Song

Keyword(s):

Missing Data ◽

Structural Equation ◽

Structural Equation Models ◽

Local Influence ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Estimation of nonlinear structural equation models with dichotomous indicator variables: a Monte Carlo comparison of methods

International Journal of Quantitative Research in Education ◽

10.1504/ijqre.2020.10028311 ◽

2020 ◽

Vol 5 (1) ◽

pp. 39

Author(s):

W. Holmes Finch

Keyword(s):

Monte Carlo ◽

Structural Equation ◽

Structural Equation Models ◽

Comparison Of Methods ◽

Nonlinear Structural ◽

Indicator Variables ◽

Nonlinear Structural Equation ◽

Dichotomous Indicator

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Model comparison of nonlinear structural equation models with fixed covariates

Psychometrika ◽

10.1007/bf02296651 ◽

2003 ◽

Vol 68 (1) ◽

pp. 27-47 ◽

Author(s):

Sik-Yum Lee ◽

Xin-Yuan Song

Keyword(s):

Structural Equation ◽

Model Comparison ◽

Structural Equation Models ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Linear indices in nonlinear structural equation models: best fitting proper indices and other composites

Quality & Quantity ◽

10.1007/s11135-010-9359-z ◽

2011 ◽

Vol 45 (6) ◽

pp. 1505-1518 ◽

Author(s):

Theo K. Dijkstra ◽

Jörg Henseler

Keyword(s):

Structural Equation ◽

Structural Equation Models ◽

Nonlinear Structural ◽

Best Fitting ◽

Nonlinear Structural Equation

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Analysis of Generalized Nonlinear Structural Equation Models by Using Bayesian Approach with Application

Pakistan Journal of Statistics and Operation Research ◽

10.18187/pjsor.v13i1.1303 ◽

2017 ◽

Vol 13 (1) ◽

pp. 17

Author(s):

Thanoon Y. Thanoon ◽

Robiah Adnan

Keyword(s):

Bayesian Approach ◽

Structural Equation ◽

Structural Equation Models ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Kernel method to estimate nonlinear structural equation models

Quality & Quantity ◽

10.1007/s11135-021-01274-9 ◽

2021 ◽

Author(s):

Ahmed Ouazza ◽

Noureddine Rhomari ◽

Zoubir Zarrouk

Keyword(s):

Structural Equation ◽

Structural Equation Models ◽

Kernel Method ◽

Nonlinear Structural ◽

Nonlinear Structural Equation

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Maximum Likelihood Methods in Treating Outliers and Symmetrically Heavy-Tailed Distributions for Nonlinear Structural Equation Models with Missing Data

Psychometrika ◽

10.1007/s11336-006-1264-1 ◽

2006 ◽

Vol 71 (3) ◽

pp. 565-585 ◽

Author(s):

Sik-Yum Lee ◽

Ye-Mao Xia

Keyword(s):

Missing Data ◽

Maximum Likelihood ◽

Structural Equation ◽

Structural Equation Models ◽

Likelihood Methods ◽

Nonlinear Structural ◽

Heavy Tailed Distributions ◽

Maximum Likelihood Methods ◽

Heavy Tailed ◽

Nonlinear Structural Equation

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