In the presence of nuisance parameters, the asymptotic loss of the maximum likelihood estimator of an interest parameter was discussed by Akahira and Takeuchi (1982) and Akahira (1986) under suitable regularity conditions from the viewpoint of higher order asymptotics. On the other hand, in statistical estimation in multiparameter cases, the conditional likelihood method is well known as a way ...

An attempt was made to compensate for the lack of long hydrological time series and the lack of information on maximum streamflow in the Alzette River basin (Luxembourg) via the regionalization of stormflow coefficients. Streamflow data recorded since 1995 with a very dense streamgauge network allowed the determination of maximum stormflow coefficients in 18 sub-basins of the Alzette. The storm...

At the previous Ionospheric Effects Symposium, we presented an extension of the phase screen theory of ionospheric scintillation for the case where the refractive index irregularities follow a two-component power law spectrum. A specific normalization was invoked to achieve a universal scaling, such that different combinations of perturbation strength, propagation distance, and frequency produc...

Change point estimation is as an effective method for identifying the time of a change in production and service processes. In most of the statistical quality control literature, it is usually assumed that the quality characteristic of interest is independently and identically distributed over time. It is obvious that this assumption could be easily violated in practice. In this paper, we use m...

this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

in this paper a novel hybrid algorithm for harmonics estimation in power systems is proposed. the estimation of the harmonic components is a nonlinear problem due to the nonlinearity of phase of sinusoids in distorted waveforms. most researchers implemented nonlinear methods to extract the harmonic parameters. however, nonlinear methods for amplitude estimation increase time of convergence. hen...

This paper provides a solution to the convergence of the parameter estimates to their true values in an ideal adaptive regulation context. The key design feature consists in the use of an asymptotically vanishing internally generated exciting sequence. 1. Introduction IN THIS paper, the following question is addressed: given a known order linear time invariant system, how does one design an ada...