scholarly journals Tumor growth modeling: Parameter estimation with Maximum Likelihood methods

2018 ◽  
Vol 160 ◽  
pp. 1-10 ◽  
Author(s):  
Spyridon Patmanidis ◽  
Alexandros C. Charalampidis ◽  
Ioannis Kordonis ◽  
Georgios D. Mitsis ◽  
George P. Papavassilopoulos
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Tumor Growth ◽  
Growth Modeling ◽  
Likelihood Methods ◽  
Maximum Likelihood Methods ◽  
Tumor Growth Modeling

scholarly journals Selecting between causal and noncausal models with quantile autoregressions

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Alain Hecq ◽  
Li Sun
Keyword(s):  
Time Series ◽  
Maximum Likelihood ◽  
Latin American ◽  
Financial Time Series ◽  
Selection Criterion ◽  
Likelihood Methods ◽  
Approximate Maximum Likelihood ◽  
Financial Time ◽  
Maximum Likelihood Methods ◽  
Latin American Countries

AbstractWe propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial time series, and is an alternative to approximate maximum likelihood methods. We illustrate our analysis using hyperinflation episodes of Latin American countries.

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