4 The parametrization based on mean and variance is a standard method within the CreditRisk+ model.
A new data transformation technique based on mean and variance of individual gas-sensor combination has been applied to improve the classification accuracy of neural network classifier.
In this case, we fixed the parameters μ and ν based on mean and variance and want to find a solution for α such that (F_{mathcal {P}_{P} alpha,mu,nu)}(14.36 =0.999).
Alternatively, distribution parameters can be also estimated based on mean and variance, which determine parameters μ and ν regarding the (mathcal {P}_{P}) parametrization and either the skewness, the kurtosis or a quantile to estimate parameter α.
Alternatively, distribution parameters can be estimated based on mean and variance, which determine parameters μ and ν regarding the (mathcal {P}_{P}) parametrization and either the skewness, the kurtosis or a quantile to estimate parameter α.
For given values t ∗>0 and p ∗∈ 0,1) the algorithm terminates if (left |F_{mathcal {P}_{P} alpha,mu,nu)}(t^ -p^right |0, whereas values for μ and ν are fixed based on mean and variance.
The uniform segmentation work based on mean and variances of motion regions.
The sample size (number of animals per treatment) chosen is based on means and variances from similar experiments with the KRN arthritis mouse model and afforded detection of 20% differences between experimental groups with a statistical power of 0.80 assuming a 2-sided alpha of <0.05.
Levene's test, based on mean or ranks, tested equality of variance.
Data are presented as mean ± standard error (SE) of mean values and tested for homogeneity of variance using Levene's test based on mean values.
