JSTOR Daily

On the Uniformly Minimum Variance Unbiased Estimators of the Variance and its Reciprocal of an Inverse Gaussian Distribution

The two-parameter inverse Gaussian distribution is found to have useful applications in a wide variety of fields. The uniformly minimum variance estimator of its mean is known and is the sample mean; ...
JSTOR Daily

An Exact Chi-Squared Decomposition Theorem for Inverse Gaussian Variates

It is proved that the scaled deviance of an inverse Gaussian sample of size n can be expressed as a sum of n - 1 independent chi-square variates. Applications to prediction intervals and squared ...
Risk

Applying the zero-adjusted inverse Gaussian model to predict probability of default and exposure at default for a credit card portfolio

Although the literature about measuring probability of default (PD) in retail credit portfolios is vast, the same thing cannot be said about measuring exposure at default (EAD). This paper aims to ...
Risk

A simple normal inverse Gaussian-type approach to calculate value-at-risk based on realized moments

Expanding the realized variance concept through realized skewness and kurtosis is a straightforward process. We calculate one-day forecasts for these moments with a simple exponentially weighted ...
Simon Fraser University

Scale Parameter

The scale parameter is 1 for Poisson and binomial distributions. SAS/INSIGHT software provides different scale parameter estimates for normal, inverse Gaussian, and gamma distributions: Note You can ...