Estimating the Weights of a Utility Function using a Bayesian Approach

Tuncer Şakar, Ceren
Yet, Barbaros


Estimating parameters in autoregressive models with asymmetric innovations
Akkaya, Ayşen (Elsevier BV, 2008-12-01)
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The number-weighted particle size distributions are difficult to be estimated experimentally. This study offers a simple conversion method to convert mass-weighted distributions to their number-weighted equivalents. Besides, the number-weighted equivalents of the Gates-Gaudin-Schuhmann, Gaudin-Meloy, Pareto, and Rosin-Rammler distributions were determined by the conversion method. The accuracy of the method was successfully confirmed on the artificial populations generated from the Gates-Gaudin-Schuhmann, R...
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Border ownership is the information that signifies which side of a border owns the border. Estimating this information has recently become very popular for perceptual organization as it allows rectification of ambigious visual information. It is applied on many computer vision problems such as object detection, depth perception and optical flow. In this thesis, two different approaches are followed to solve the border ownership problem. For the supervised approach, conditional random fields are used as it i...
Estimating the form of a decision maker's preference function and converging to preferred solutions
Köksalan, Mustafa Murat; Karakaya, Gülşah (null; 2018-11-07)
We estimate the form of an underlying preference function that is assumed to represent the preferences of a decision maker in a multi-objective environment. After estimating the form, we use an algorithm that utilizes the properties of the estimated form in order to efficiently converge to a preferred solution of the decision maker. We develop the necessary theory to estimate the form of the preference function. We test our approach on several instances and show that it works well.
Estimating parameters in autoregressive models in non-normal situations: Asymmetric innovations
Akkaya, Ayşen (2001-01-01)
The estimation of coefficients in a simple autoregressive model is considered in a supposedly difficult situation where the innovations have an asymmetric distribution. Two distributions, gamma and generalized logistic, are considered for illustration. Closed form estimators are obtained and shown to be efficient and robust. Efficiencies of least squares estimators are evaluated and shown to be very low. This work is an extension of that of Tiku, Wong and Bian [1] who give solutions for a simple AR(I) model
Citation Formats
C. Tuncer Şakar and B. Yet, “Estimating the Weights of a Utility Function using a Bayesian Approach,” 2017, Accessed: 00, 2021. [Online]. Available: