Exact(1)
(6) Y = Φ· θ + e In equation (6), the random noise ε[ t k ] is regarded as a random variables of white Gaussian noise with zero mean and unknown variance σ, i.e., E{ e} = 0, and Σ e = E{ ee T } = σ I, where I is an identity matrix.
Similar(59)
Next we model the mean parameter λ as a random variable to describe the expression variability among genes.
This effect is caused by the randomness of shadowing and is statistically modeled as a random variable χ.
As the individuals in advanced intercross generations are variably related, we furthermore included family as a random variable.
This allows us to treat θ as a random variable as in Bayesian statistics.
In (1.1), X is used as a random variable having CDF F (x) and then as a random variable having CDF G (x) which may be confusing.
In general each OD pair is considered as a random variable with a prior distribution.
The friction coefficient at large velocity is considered as a random variable.
In the process, the seismic input is also considered as a random variable.
Each of these parameters can be defined either as a random variable or as a constant quantity.
The gain itself is considered as a random variable with a given probability density function (pdf).
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