Sentence examples for mean normal distribution from inspiring English sources

N ( 0, σ 2 ) denotes a zero mean normal distribution with variance σ2.

where the real and imaginary parts obey a zero mean normal distribution with half the original variance, respectively.

where the parameters α5 is the effective attenuation constant, C5|dB is a constant and their values are listed in Table 2. χ5|dB follows a zero mean normal distribution with a SD of 4.14 dB.

where the parameter α4 is the effective attenuation constant, C4|dB is a constant and their values are listed in Table 2. χ4|dB follows a zero mean normal distribution with a SD of 2.25 dB. Figure 11 shows the Q-Q plot of the empirical quantiles of the error between the PL model and the simulated PL results on the vertical axis to a theoretical standard normal distribution on the horizontal axis.

Whatever the method used to define the prior values, we suggest checking the resulting posterior distributions in order to make sure they are evenly sampled around the specified mean (normal distribution) and not centred on the highest or lowest categories (skewed distribution).

σ ε 2 is the variance of the zero-mean normal distribution representing the residual error.

σ γ B k R 2 is the variance of the zero-mean normal distribution representing the background count rate contribution.

With these assumptions, the observation vector y[i]will also follow an n-dimensional zero-mean normal distribution with the covariance matrix R = E { y y H } = A P A H + σ 2 I (62).

μ CF is the mean, and α _CF i is the random intercept representing a contribution specific to calibration source i. σ C F 2 is the variance of the zero-mean normal distribution of the random intercept.

Assume that the process X t is monitored by a control chart that signals at time T. We assign a zero-mean normal distribution with a standard deviation of 6 × λ 0 as a prior distribution for all change sizes (δ, β, δ1, δ2).

where X_{k}=left[ begin{array}{c} mathcal{X}_{k} dot{mathcal{X}_{k}} end{array} right], quad F=left[begin{array}{c} I_{n} 0_{n,n} end{array}right], w k is a zero-mean normal distribution associated with the random noise of the proposed dynamic model and n represents the number of observed dimensions of the environment as shown in Eq. (2).