Abstract
Confidence intervals describe a range of the variable that is estimated to have a given probability of occurrence. When the distribution is known, a confidence interval is immediately calculated from the mathematical properties of the probability distribution. A more complex task is the estimation of confidence intervals for parameters of a distribution based on available data. The method of fiducial inference makes it possible to estimate confidence intervals of unknown parameters based on the distribution of a statistic used to estimate the parameter. Bayesian methods of inference use prior distributions to determine the posterior distribution of a parameter based on the information provided by the data.
Published Version
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