Hypothesis Testing for Fractional Stochastic Partial Di erential Equations with Applications to Neurophysiology and Finance
Journal Title: Asian Research Journal of Mathematics - Year 2017, Vol 4, Issue 1
Abstract
The paper obtains explicit form of fine large deviation theorems for the log-likelihood ratio in testing fractional stochastic partial differential equation models using a finite number of Fourier coefficients of the solution. The equation is driven by additive noise that is white in space and colored (fractional) in time with Hurst parameter H ≥ 1/2. It obtains explicit rates of decrease of the error probabilities of Neyman-Pearson, Bayes and minimax tests. Finally, it provides several examples including two practical examples of membrane voltage model from neurophysiology and forward interest rate model from finance.
Authors and Affiliations
Jaya P. N. Bishwal
Keywords
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- EP ID EP338358
- DOI 10.9734/ARJOM/2017/33094
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