A simple connection between the Bartlett adjustment factor of the log likelihood ratio statistic and the normalizing constant of the p∗ formula–an approximate conditional density for the maximum likelihood estimate given an exact or an approximate ancillary statistic–was established...

In this paper, a new approximation of the marginal posterior distribution function is obtained. Moreover, for the location-scale model, by applying the shrinkage argument, a new approximation of the conditional distribution function of the signed likelihood ratio statistic given an ancillary...

A simple normal approximation for the cumulative distribution function of the F distribution is obtained via a general version of the modified signed log-likelihood ratio statistic. This approximation exhibits remarkable accuracy even when the degrees of freedom are small. Using the same...

Longitudinal studies are often conducted to explore the cohort and age effects in many scientific areas. The within cluster correlation structure plays a very important role in longitudinal data analysis. This is because not only can an estimator be improved by incorporating the within cluster...

Longitudinal studies are often conducted to explore the cohort and age effects in many scientific areas. The within cluster correlation structure plays a very important role in longitudinal data analysis. This is because not only can an estimator be improved by incorporating the within cluster...

A proportional hazard function together with partial likelihood estimation is the most common approach to the analysis of censored data. However, partial likelihood estimation is established on the grounds that the censoring is non-informative. The partial likelihood approach enjoys many good...

Testing for first-order autocorrelation in small samples using the standard asymptotic test can be seriously misleading. Recent methods in likelihood asymptotics are used to derive more accurate p-value approximations for testing the autocorrelation parameter in a regression model. The methods...

In this paper, a general worst case stopping scenario for vehicle following is used to develop algorithms for generating the minimum safety spacing (MSS) for collision-free vehicle following. These algorithms are used to study the effects of vehicle characteristics and other parameters on the...