Pairwise likelihood estimation for the normal ogive model with binary data

2015 ◽  
Vol 100 (2) ◽  
pp. 223-237
Author(s):  
M.-L. Feddag
Keyword(s):  
Binary Data ◽  
Likelihood Estimation ◽  
Pairwise Likelihood ◽  
Normal Ogive Model

scholarly journals Pairwise likelihood estimation of latent autoregressive count models

2020 ◽  
Vol 29 (11) ◽  
pp. 3278-3293
Author(s):  
Xanthi Pedeli ◽  
Cristiano Varin
Keyword(s):  
Likelihood Function ◽  
Likelihood Estimation ◽  
Autoregressive Models ◽  
Suggested Approach ◽  
Pairwise Likelihood ◽  
Simulation Based ◽  
Likelihood Approach ◽  
Computationally Intensive ◽  
Methodological Aspects

Latent autoregressive models are useful time series models for the analysis of infectious disease data. Evaluation of the likelihood function of latent autoregressive models is intractable and its approximation through simulation-based methods appears as a standard practice. Although simulation methods may make the inferential problem feasible, they are often computationally intensive and the quality of the numerical approximation may be difficult to assess. We consider instead a weighted pairwise likelihood approach and explore several computational and methodological aspects including estimation of robust standard errors and the role of numerical integration. The suggested approach is illustrated using monthly data on invasive meningococcal disease infection in Greece and Italy.

scholarly journals Pairwise likelihood estimation for factor analysis models with ordinal data

2012 ◽  
Vol 56 (12) ◽  
pp. 4243-4258 ◽  
Author(s):  
Myrsini Katsikatsou ◽  
Irini Moustaki ◽  
Fan Yang-Wallentin ◽  
Karl G. Jöreskog
Keyword(s):  
Factor Analysis ◽  
Ordinal Data ◽  
Likelihood Estimation ◽  
Pairwise Likelihood ◽  
Analysis Models
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