Although considerable attention has recently been paid to the behavior of the maximum likelihood estimator of simple moving average models, little progress has been made in finding a good approximation to its distribution in cases where the process is close to being noninvertible. In this paper a method is produced that gives an excellent approximation to the distribution function, even in the case where the process is strictly noninvertible. Also studied is the related problem of the distribution of the maximum likelihood estimator of the signal-to-noise ratio in the local level model
We consider the problem of estimating the distribution function, the density and the hazard rate of ...
The likelihoood function of the Gaussian MA(1) zero-mean can be expressed in terms of the variance o...
International audienceThis paper is devoted to the computation of the maximum likelihood estimates o...
Although considerable attention has recently been paid to the behavior of the maximum likelihood est...
A limit theory was developed in the papers of Davis and Dunsmuir (1996) and Davis et al. (1995) for ...
Dealing with noninvertible, infinite-order moving average (MA) models, we study the asymptotic prope...
A limit theory was developed in the papers of Davis and Dunsmuir (1996) and Davis et al. (1995) for ...
A procedure for solving exact maximum likelihood estimation (MLE) is proposed for non-invertible non...
[[abstract]]A procedure for computing exact maximum likelihood estimates (MLEs) is proposed for non-...
A local level model has a deterministic level when the signal-to-noise ratio q is zero. In this pape...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
We consider an approximate maximum likelihood algorithm for estimating parameters of possibly non-ca...
In this paper, we examine some problems that the sampling fluctuation of the estimated autocorrelati...
Diffusion models have been used extensively in many applications. These models, such as those used i...
The local maximum likelihood estimate (t) of a parameter in a statistical model f(x, theta) is defin...
We consider the problem of estimating the distribution function, the density and the hazard rate of ...
The likelihoood function of the Gaussian MA(1) zero-mean can be expressed in terms of the variance o...
International audienceThis paper is devoted to the computation of the maximum likelihood estimates o...
Although considerable attention has recently been paid to the behavior of the maximum likelihood est...
A limit theory was developed in the papers of Davis and Dunsmuir (1996) and Davis et al. (1995) for ...
Dealing with noninvertible, infinite-order moving average (MA) models, we study the asymptotic prope...
A limit theory was developed in the papers of Davis and Dunsmuir (1996) and Davis et al. (1995) for ...
A procedure for solving exact maximum likelihood estimation (MLE) is proposed for non-invertible non...
[[abstract]]A procedure for computing exact maximum likelihood estimates (MLEs) is proposed for non-...
A local level model has a deterministic level when the signal-to-noise ratio q is zero. In this pape...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
We consider an approximate maximum likelihood algorithm for estimating parameters of possibly non-ca...
In this paper, we examine some problems that the sampling fluctuation of the estimated autocorrelati...
Diffusion models have been used extensively in many applications. These models, such as those used i...
The local maximum likelihood estimate (t) of a parameter in a statistical model f(x, theta) is defin...
We consider the problem of estimating the distribution function, the density and the hazard rate of ...
The likelihoood function of the Gaussian MA(1) zero-mean can be expressed in terms of the variance o...
International audienceThis paper is devoted to the computation of the maximum likelihood estimates o...