SUMMARYThis paper considers an asymptotic distribution for an estimateŜ pk of the process yield index S pk proposed by Boyles (1994). The asymptotic distribution ofŜ pk is useful in statistical inferences for S pk . An illustrative example is given for hypothesis testing and for interval estimation on the yield index S pk .
Consistent perturbation theory for thermodynamical quantities in strongly type-II superconductors in a magnetic field at low temperatures is developed. It is complementary to the existing expansion valid at high temperatures. Magnetization and specific heat are calculated to two-loop order and compare well with existing Monte Carlo simulations, other theories, and experiments.
In this paper we consider from maximum likelihood and Bayesian points of view the generalized growth curve model when the covariance matrix has a Toeplitz structure. This covariance is a generalization of the AR(1) dependence structure. Inferences on the parameters as well as the future values are included. The results are illustrated with several real data sets.
The power transformation of Box and Cox (1964) has been shown to be quite useful in short-term forecasting for the linear regression model with AR(1) dependence structure (see, for example, Lu, 1987, 1989). It is crucial to have good estimates of the power transformation and serial. correlation parameters, because they form the basis for estimating other parameters and predicting future observations. The prediction of future observations is the main focus of this paper. We propose to estimate these two parameters by minimizing the mean squared prediction errors. These estimates and the corresponding predictions compare favourably, via revs and simulated data, with those obtained by the maximum likelihood method. Similar results are also demonstrated in the repeated measurements setting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.