Statistical Computing
farzad eskandari
Abstract
Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable ...
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Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable model is presented toestimate the parameters of the interval generalized linear model. The two models are provided on the basis ofthe interval arithmetic. The estimation procedure of the parameters of the suitable model is as the estimationprocedure of the parameters of the interval generalized linear model. The least-squares (LS) estimation of thesuitable model is developed according to a nice distance in the interval space. The LS estimation is resolvedanalytically through a constrained minimization problem. Then some desirable properties of the estimatorsare checked. Finally, both the theoretical and the empirical performance of the estimators are investigated.
Statistical Simulation
farzad eskandari
Abstract
Imprecise measurement tools produce imprecise data. Interval-valued data is usually used to deal with such imprecision. So interval-valued variables are used in estimation methods. They have recently been modeled by linear regression models. If response variable has any statistical distributions, interval-valued ...
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Imprecise measurement tools produce imprecise data. Interval-valued data is usually used to deal with such imprecision. So interval-valued variables are used in estimation methods. They have recently been modeled by linear regression models. If response variable has any statistical distributions, interval-valued variables are modeled in generalized linear models framework. In this article, we propose a new consistent estimator of a parameter in generalized linear models with regard to distributions of response variable in the exponential family. A simulation study shows that the new estimator is better than others on the basis of particular distributions of response variable. We present optimal properties of the estimators in this research