




Volume 28 • Number 2 • 2005 

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Approximating Fisher's Information for the Replicated Linear Circular
Functional Relationship Model
Abdul Ghapor Hussin 
Abstract.
The problem that this paper attempting to solve is the derivation of
Fisher's information matrix using four parameters which are two error
concentration parameters of variables, intercept and slope parameter for
the replicated linear circular functional relationship model. The model
is formulated assuming both variables are circular, subject to errors
and there is a linear relationship between them. The maximum likelihood
estimation have been used to estimate all the parameters. It is shown
that estimate of Fisher's information can be obtained by using various
theories of matrices and approximation of the asymptotic properties of
Bassel function.
2000
Mathematics Subject Classification: 62E17
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