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We used the joint adaptive mean variance regularization procedure recently introduced by Dazard and Rao (16).
λ is a mean, variance, and mixture weight of GMM.
Let,, and represent the (mean, variance) of distribution,, and, respectively.
These statistics include the mean, variance, zero-crossing rate, entropy, and auto-correlation with template signals.
The mean, variance, and the moment of order are given, respectively, by (7).
As a result, the output PDF rather than the mean variance was proposed [16 18].
Similar(28)
They use arguments from a mean-variance utility approach.
As an extension of the fuzzy mean-variance model, a mean-variance-skewness model is presented and the corresponding variations are also considered.
The mean-variance approach is based on an underlying Euclidean-geometry perspective.
Section "Two-period mean-variance analysis" presents an analysis of the problem from the mean-variance perspective developing the two-period portfolio theory along with the two-period mean-variance frontier and the procedures for its computation.
We base our analysis on the mean-variance expected utility model with entry costs.
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