We investigate the Bayesian framework for detection of continuous gravitational waves (GWs) in the context of targeted searches, where the phase evolution of the GW signal is assumed to be known, while the four amplitude parameters are unknown. We show that the orthodox maximum-likelihood statistic (known as F-statistic) can be rediscovered as a Bayes factor with an unphysical prior in amplitud...

This paper is concerned with the power of tests for regime switching. Asymptotic results are currently available only for the null distribution, and this distribution is dependent on the underlying parameter space. This paper addresses the lack of asymptotic results. The asymptotic behavior of the test statistic is determined under a full range of drifting sequences of true distributions. The r...

Let f be a probability density on the real line, let n be any positive integer, and assume the condition (R) that log f is locally integrable with respect to Lebesgue measure. Then either log f is almost everywhere equal to a polynomial of degree less than n, or the order statistic of n independent and identically distributed observations from the location-scale parameter model generated by f i...

The von Mises distribution is often useful for modelling circular data problems. We consider a model for which von Mises data is contaminated with a certain proportion of points uniformly distributed around the circle. Maximum likelihood estimation is used to produce parameter estimates for this mixture model. Computational issues involved with obtaining the maximum likelihood estimates for the...

This paper presents a set of REDUCE procedures that make a number of existing higher-order asymptotic results available for both theoretical and practical research. Attention has been restricted to the context of exact and approximate inference for a parameter of interest conditionally either on an ancillary statistic or on a statistic partially suucient for the nuisance parameter. In particula...

Panel estimators can provide consistent measures of a long-run average parameter even if the individual regressions are spurious. However, the t-test on this parameter is fraught with problems because the limit distribution of the test statistic is non-standard and rather complicated, particularly in panels with mixed (non-)stationary errors. A sieve bootstrap framework is suggested to approxim...

A bstract-We discuss the problem of testing for constant versus time varying regression coefficients. Our alternative hypothesis allows the coefficients to follow a stationary AR(1) process with unknown autoregressive parameter. Standard testing procedures are inappropriate since this parameter is identified only under the alternative. We propose a test statistic which is a function of a sequen...

This paper derives asymptotic power functions for Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequalities in the case where the parameter is set identified. Combined with power results for Kolmogorov-Smirnov (KS) tests, these results can be used to choose the optimal test statistic, weighting function and, for tests based on ...

This research considers a multiple multivariate linear regression model with a parameter matrix some of the rows of which are constrained by synchronized order restrictions. The test on the homogeneity of the parameter matrix is considered. Under the assumption that the common variance covariance matrix is unknown, an ad-hoc test statistic is proposed by replacing the unknown covariance matrix ...

This paper is concerned with the power of tests for regime switching. Asymptotic results are currently available only for the null distribution, and this distribution is dependent on the underlying parameter space. This paper addresses the lack of asymptotic results. The asymptotic behavior of the test statistic is determined under a full range of drifting sequences of true distributions. The r...