Power transformations to induce normality and their applications

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Box–Cox transforms for realized volatility (2011, background): “More recently, Chen and Deo (2004) propose power transformations for statistics that are positive linear combinations of positive independent ran- dom variables, thus generalizing the Wilson and Hilferty (1931) power transformation.”
The log of the determinant of the autocorrelation matrix for testing goodness of fit in time series (2006, background): “(ii)As the eigenvalues of the covariance matrix are approximately equal to the power spectrum ordinates at the frequencies i = 2 i/m, (see Hannan, 1970), the statistic is also approximately D∗m ≈ −T (m+1)−1 ∑ log f ( i ) where f ( i ) is the spectral density.”
VARIANCE-RATIO TESTS OF RANDOM WALK: AN OVERVIEW (2009, unknown): “The VR estimator is defined as V R(k) = 1+2 T−1 ∑ i=1 h(i/k)ρ̂(i), (14)”
A GENERALIZED PORTMANTEAU TEST FOR INDEPENDENCE BETWEEN TWO STATIONARY TIME SERIES (2008, methodology): “However, our work differs from Chen and Deo (2004a) in two important aspects.”