We use moderate deviations to study the signal detection problem for a diffusion model.We establish a moderate deviation principle for the log-likelihood function of the diffusion model.Then applying the moderate devi...We use moderate deviations to study the signal detection problem for a diffusion model.We establish a moderate deviation principle for the log-likelihood function of the diffusion model.Then applying the moderate deviation estimates to hypothesis testing for signal detection problem we give a decision region such that its error probability of the second kind tends to zero with faster speed than the error probability of the first kind when the error probability of the first kind is approximated by e-αr(T),where α>0,r(T)=o(T) and r(T) →∞ as the observation time T goes to infinity.展开更多
This paper studies hypothesis testing in the Ornstein-Ulenbeck process with linear drift. With the help of large and moderate deviations for the log-likelihood ratio process, the decision regions and the corresponding...This paper studies hypothesis testing in the Ornstein-Ulenbeck process with linear drift. With the help of large and moderate deviations for the log-likelihood ratio process, the decision regions and the corresponding decay rates of the error probabilities related to this testing problem are established.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos.10871153 and 11171262)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200804860048)
文摘We use moderate deviations to study the signal detection problem for a diffusion model.We establish a moderate deviation principle for the log-likelihood function of the diffusion model.Then applying the moderate deviation estimates to hypothesis testing for signal detection problem we give a decision region such that its error probability of the second kind tends to zero with faster speed than the error probability of the first kind when the error probability of the first kind is approximated by e-αr(T),where α>0,r(T)=o(T) and r(T) →∞ as the observation time T goes to infinity.
文摘This paper studies hypothesis testing in the Ornstein-Ulenbeck process with linear drift. With the help of large and moderate deviations for the log-likelihood ratio process, the decision regions and the corresponding decay rates of the error probabilities related to this testing problem are established.
