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İktisat Bölümü

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Browsing İktisat Bölümü by Journal "Journal of Applied Statistics"

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    Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Inference in Multivariate Linear Regression Models With Elliptically Distributed Errors
    (Taylor & Francis Ltd, 2014) Yazici, Mehmet; Islam, M. Qamarul; Yildirim, Fetih
    In this study we investigate the problem of estimation and testing of hypotheses in multivariate linear regression models when the errors involved are assumed to be non-normally distributed. We consider the class of heavy-tailed distributions for this purpose. Although our method is applicable for any distribution in this class, we take the multivariate t-distribution for illustration. This distribution has applications in many fields of applied research such as Economics, Business, and Finance. For estimation purpose, we use the modified maximum likelihood method in order to get the so-called modified maximum likelihood estimates that are obtained in a closed form. We show that these estimates are substantially more efficient than least-square estimates. They are also found to be robust to reasonable deviations from the assumed distribution and also many data anomalies such as the presence of outliers in the sample, etc. We further provide test statistics for testing the relevant hypothesis regarding the regression coefficients.
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    Article
    Citation - WoS: 13
    Citation - Scopus: 13
    Multiple Linear Regression Model With Stochastic Design Variables
    (Taylor & Francis Ltd, 2010) Islam, M. Qamarul; Tiku, Moti L.
    In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.