Characterization of inverse-Gaussian and gamma distributions through their length-biased distributions

For the case where Y is a length-biased random variable corresponding to a random variable X having an inverse-Gaussian or gamma distribution, it is shown that Y can be written as a linear combination of X and a chi-square random variable and, conversely, X can be characterized through this relationship. Finally, the Wald distribution is characterized