Performance evaluation of the non-linear and linear estimation methods for determining kinetic parameters in dynamic FDG-PET study

2010 ◽  
Author(s):  
Xiaoqian Dai ◽  
Jie Tian ◽  
Zhe Chen
Keyword(s):  
Performance Evaluation ◽  
Kinetic Parameters ◽  
Fdg Pet ◽  
Estimation Methods ◽  
Linear Estimation ◽  
Non Linear

Performance evaluation of a non-linear error model for underwater range computation utilizing GPS sonobuoys

2010 ◽  
Vol 19 (7) ◽  
pp. 1057-1067 ◽  
Author(s):  
Ahmed El-Shafie ◽  
Abdalla Osman ◽  
Aboelmagd Noureldin ◽  
Aini Hussain
Keyword(s):  
Performance Evaluation ◽  
Error Model ◽  
Non Linear ◽  
Range Computation

scholarly journals Autoregressive Models of the Random fields—A Survey

2020 ◽  
pp. 1-9
Keyword(s):  
Random Fields ◽  
Linear Models ◽  
Estimation Methods ◽  
Suitable Model ◽  
Main Mode ◽  
One Dimensional ◽  
Non Linear ◽  
The Status ◽  
Ar Models ◽  
Shed Light

Autoregressive (AR) random fields are widely use to describe changes in the status of real-physical objects and implemented for analyzing linear & non-linear models. AR models are Markov processes with a higher order dependence for one-dimensional time series. Actually, various estimation methods were used in order to evaluate the autoregression parameters. Although in many applications background knowledge can often shed light on the search for a suitable model, but other applications lack this knowledge and often require the type of trial errors to choose a model. This article presents a brief survey of the literatures related to the linear and non-linear autoregression models, including several extensions of the main mode models and the models developed. The use of autoregression to describe such system requires that they be of sufficiently high orders which leads to increase the computational costs.

scholarly journals Non linear estimation of returns on hedge funds with scarce observations

2021 ◽  
Author(s):  
Akram Samarikhalaj
Keyword(s):  
Hedge Funds ◽  
Linear Estimation ◽  
Non Linear

Non linear estimation of returns on hedge funds with scarce observations

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