Sentence examples for variance density from inspiring English sources

The energy period (T_mathrm{e}) which is the variance-weighted mean period of the non-directional variance density spectrum is calculated from the spectral moments as follows: begin{aligned} T_mathrm{e}=frac{m_{-1}}{m_{0}}.

The spectral estimate of significant wave height can be estimated from the zeroth moment of variance spectrum (m_{0}) as follows: begin{aligned} H_{m0}=4sqrt{m_{0}}. end{aligned} (1 For the non-directional variance density spectrum, the spectral moment of (nmathrm{th}) order, (m_{n}), is calculated using the following equation.

begin{aligned} m_{n}=sum _{i=1}^{n}{f_{i}}^n E_{i}Delta f, end{aligned} (2 where ({f_{i}}^n) is the (i th frequency corresponding to the (n th order, (Delta f) is the frequency increment and (E_{i}) is the sea surface variance density over a range of wave frequencies i.

First, they offer a unified view of currently separated theories relating environmental variance, density-dependent processes and assemblage dynamics [31], [39], [40].

Scale parameters for maternal permanent environmental and error variances densities were then set according to the REML estimates.

In draw two, three, and four there is a difference in the level-1 (within person) variance posterior density, but no large difference for the level-2 (between person) variance posterior density.

At variance, lower density foams display a quasi-linear behavior up to 35% strain.

In all cases the mean and variance of density are captured correctly by the stochastic hybrid algorithm.

In all cases the mean and variance of density and velocity are captured correctly by the stochastic hybrid algorithm.

The percentage variance in density explained by reader differences was estimated to be 11%%.

We apply exponential tilts to (i) the distribution of the natural sufficient statistics of the systematic risk factors and (ii) conditional default probabilities, given the simulated values of the systematic risk factors, and select parameter values by minimizing the Kullback Leibler divergence of the resulting parametric family from the ideal (zero-variance) importance density.