Sentence examples for normal density for from inspiring English sources

A normal density for the individual specific random effect is assumed.

The two-dimensional standard normal density for example has circular level curves centered at the origin.

Assuming that the distribution of the residuals is normal with mean zero and variance, then the likelihood of model (1) is where denotes a normal density for random variable y i centered at and with variance.

Cragg suggested the probit link for modeling the binary part and a truncated normal density for the positive values, allowing a different set of covariates to be associated with the probability of having a non-zero response and the magnitude of the positive response respectively.

We assume a multivariate normal density for the phenotype vector y i with genotype-specific means (5) μ k   = [ μ k (1, 1 ),..., μ k (1, T ), ︸ irradiance 1...  , [ μ k (S, 1 ),..., μ k (S, T ) ', ︸ irradiance S and covariance matrix Σ = cov y i).

Rather, we used population densities that were far above normal density thresholds for sex induction, in order to exclude the possibility of erroneously assigning OP to clones that just did not receive a sufficiently strong cue.

The basis for developing this is to use the reproportioning method, which has already been developed for proportioning normal density cement concrete mixes, for SFRC mixes.

Figure 1 shows the histogram and the normal density function of sulfamethoxazole for natural and waste-waters and the LOEC and EC50 for different species [see Supplemental Material, Table 2 (available online at http://www.ehponline.org/members/2009/11776/suppl.pdf)].

The starting point was the methodology proposed by Nepomuceno et al. (2014) for normal density self-compacting concrete (SCC).

The full density factors into independent multivariate normal densities (MVNs) for each row of Λ k * : π (λ j | y j, b j, e a j, F, ψ r j ) ∼ N (ψ r j − 1 C − 1 F T (y j − X b j − Z e a j ), C − 1 ), where C = ψ r j − 1 F T F + Diag (φ i j τ j ).

where = D denotes convergence in distribution, C N μ,Γ,C) stands for a complex normal density where μ is the location parameter, Γ is the covariance matrix, and C is the relation matrix [14].