Ekonomi Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/818

Browse

Now showing 1 - 3 of 3

Citation Count: Islam, MQ; Tiku, ML; Yıldırım F., "Nonnormal regression. i. skew distributions" Communications In Statistics-Theory And Methods, Vol.30, No.6, pp.993-1020, (2001).
Nonnormal regression. i. skew distributions
(Marcel Dekker Inc, 2001) Islam, M. Qamarul; Tiku, M. L.; Yıldırım, F.
In a linear regression model of the type y = thetaX + e, it is often assumed that the random error e is normally distributed. In numerous situations, e.g., when y measures life times or reaction times, e typically has a skew distribution. We consider two important families of skew distributions, (a) Weibull with support IR: (0, infinity) on the real line, and (b) generalised logistic with support IR: (-infinity, infinity). Since the maximum likelihood estimators are intractable in these situations, we derive modified likelihood estimators which have explicit algebraic forms and are, therefore, easy to compute. We show that these estimators are remarkably efficient, and robust. We develop hypothesis testing procedures and give a real life example.
Citation Count: Tiku, ML; Islam, MQ; Selcuk, AS, "Nonnormal regression. II. Symmetric distributions", Communications in Statistics-Theory and Methods, Vol. 30, No. 6, pp. 1021-1045, (2001).
Nonnormal regression. II. Symmetric distributions
(Taylor&Francis INC, 2001) Tiku, M. L.; Islam, M. Qamarul; Selçuk, A. S.
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 likelihood is used to derive MML estimators of parameters in a linear regression model. The estimators are shown to be efficient, and robust to inliers. This paper is essentially the first to achieve robustness to infers. The methodology is extended to long-tailed symmetric distributions and the resulting estimators are shown to be efficient, and robust to outliers. This paper should be read in conjunction with Islam et al. [2] who develop modified likelihood methodology for skew distributions in the context of linear regression.
Citation Count: Sazak, H., Tiko, ML., Islam, MQ. (2006). Regression analysis with a dtochastic design variable. International Statistical Review, 74(1), 77-88.
Regression analysis with a dtochastic design variable
(In Statistical Inst, 2006) Sazak, Hakan; Tiku, Moti L.; S., Hakan; Islam, M. Qamarul
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 situations are considered. Real life examples are given

Browse

Browsing Ekonomi Bölümü Yayın Koleksiyonu by Author "Islam, M. Qamarul"