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Konu "Modified Likelihood" için listeleme

Konu "Modified Likelihood" için listeleme

Sırala: Sıra: Sonuçlar:

  • Estimating parameters of a multiple aoutoregressive model by the modified maximum likelihood method 
    Türker Bayrak, Özlem; Dener Akkaya, Ayşen (Elsevier Science, 2010-02)
    Abstract: We consider a multiple autoregressive model with non-normal error distributions, the latter being more prevalent in practice than the usually assumed normal distribution. Since the maximum likelihood equations ...
  • Linear contrasts in one-way classification AR(1) model with gamma innovations 
    Şenoğlu, Birdal; Bayrak, Özlem Türker (Hacettepe Univ, Fac Sci, 2016-12)
    In this study, the explicit estimators of the model parameters in oneway classification AR(1) model with gamma innovations are derived by using modified maximum likelihood (MML) methodology. We also propose a new test ...
  • Multiple linear regression model under nonnormality 
    Islam, M. Q.; Tiku, M. L. (2004-10)
    We consider multiple linear regression models under nonnormality. We derive modified maximum likelihood estimators (MMLEs) of the parameters and show that they are efficient and robust. We show that the least squares ...
  • Multiple linear regression model under nonnormality 
    Islam, M. Qamarul; Tiku, Moti L. (2004-10)
    We consider multiple linear regression models under nonnormality. We derive modified maximum likelihood estimators (MMLEs) of the parameters and show that they are efficient and robust. We show that the least squares ...
  • Nonnormal regression. II. Symmetric distributions 
    Tiku, M. L.; Islam, M. Qamarul; Selçuk, A. S. (Taylor&Francis INC, 2001)
    Salient features of a family of short-tailed symmetric distributions, introduced recently by Tiku and Vaughan [1], are enunciated. Assuming the error distribution to be one of this family, the methodology of modified ...
  • Regression analysis with a dtochastic design variable 
    Sazak, Hakan; Tiku, Moti L.; S., Hakan; Islam, M. Qamarul (In Statistical Inst, 2006-04)
    In regression models, the design variable has primarily been treated as a nonstochastic variable. In numerous situations, however, the design variable is stochastic. The estimation and hypothesis testing problems in such ...