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Optimal design theory is developed for an inverse Gaussian regression model in which the reciprocal mean is a polynomial function of a concomitant variable. Comparisons are made to the traditional normal theory optimal designs for linear and nonlinear regression.
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Bayesian analysis of system failure data from engineering applications under a competing risks framework is considered when the cause of failure may not have been exactly identified but has only been narrowed down to a subset of all potential risks. In statistical literature, such data are...
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The linearity (or lack thereof) of association between sample mean and sample variance is explored in this note with the intent of providing new insights. Of particular interest is a well-known inequality involving the measures of skewness and kurtosis that is derived as a consequence of an...
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