Joint maximum likelihood estimation of unit root testing equations and GARCH processes: Some finite-sample issues

2008 ◽  
Vol 77 (1) ◽  
pp. 109-116 ◽  
Author(s):  
Steven Cook
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Unit Root ◽  
Likelihood Estimation ◽  
Finite Sample ◽  
Unit Root Testing ◽  
Joint Maximum Likelihood Estimation ◽  
Garch Processes

On the Relationships between Sum Score Based Estimation and Joint Maximum Likelihood Estimation

Psychometrika ◽  
2007 ◽  
Vol 73 (1) ◽  
pp. 145-151 ◽  
Author(s):  
Guido del Pino ◽  
Ernesto San Martín ◽  
Jorge González ◽  
Paul De Boeck
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Joint Maximum Likelihood Estimation ◽  
Sum Score

scholarly journals Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes

Bernoulli ◽  
2004 ◽  
Vol 10 (4) ◽  
pp. 605-637 ◽  
Author(s):  
Christian Francq ◽  
Jean-Michel Zakoïan
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Garch Processes

scholarly journals The Kumaraswamy Exponentiated U-Quadratic Distribution: Properties and Application

2018 ◽  
pp. 1-17
Author(s):  
Mustapha Muhammad ◽  
Isyaku Muhammad ◽  
Aisha Muhammad Yaya
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Quantile Function ◽  
Moment Generating Function ◽  
Maximum Likelihood Estimates ◽  
Alternative Methods ◽  
Finite Sample ◽  
Modified Maximum Likelihood ◽  
Probability Weighted Moments

In this paper, a new lifetime model called Kumaraswamy exponentiated U-quadratic (KwEUq) distribution is proposed. Several mathematical and statistical properties are derived and studied such as the explicit form of the quantile function, moments, moment generating function, order statistics, probability weighted moments, Shannon entropy and Renyi entropy. We also found that the usual maximum likelihood estimates (MLEs) fail to hold for the KwEUq distribution. Two alternative methods are suggested for the parameter estimation of the KwEUq, the alternative maximum likelihood estimation (AMLE) and modified maximum likelihood estimation (MMLE). Simulation studies were conducted to assess the finite sample behavior of the AMLEs and MMLEs. Finally, we provide application of the KwEUq for illustration purposes.

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