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Its mean and variance are both equal to μt.
In this paper, explicit formulas for this variance are presented.
Assignment probabilities which minimize the asymptotic variance are obtained.
where the mean and the variance are given by (29).
where the mean and the variance are defined as (38).
Predictions of the stationary variance are compared with Monte Carlo simulations.
The best combinations of covariates for the mean and variance are selected using Akaike's information criterion.
Transient response statistics such as the mean value and the variance are evaluated numerically.
DOE (Design of Experiments) and ANOVA (Analysis of Variance) are used to rank the parameter effects.
Mean and variance are statistically significant features, while skewness and kurtosis are not.
Taguchi method and analysis of variance are used for the simulation design and data analysis, respectively.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com