A time series must be stationary, i.e., one which has a constant mean, variance, and autocorrelation function, in order for an ARIMA model to be applicable.
λ is a mean, variance, and mixture weight of GMM.
The mean, variance, and the moment of order are given, respectively, by (7).
μ, σ2, and σ xy are the mean, variance, and cross covariance, respectively.
The mean, variance, and the moment of order of Nakagami distribution are given, respectively by (11).
for the mean, variance, and the fourth central moment of, and assume that.
The other (K−1) distributions would have their mean, variance and weight kept the same.
Further, the mean, variance, and standard deviation are measured using Eqs.
This usually includes calculation and interpretation of the mean, variance and confidence limit of a population.
Lower mean, variance, and standard deviation of queue delay represent a steadier queue delay for the algorithm.
Three features, mean, variance, and zero crossing rate are computed on the magnitude of the 3-axis acceleration.
