The expectations are obtained using the formulas: cf I, u = ∑ j ∑ e, d ∑ < e, d > → i ; i ∈ I, u c i · p e, d, j, i cg I, T = ∑ j ∑ e, d ∑ < e, d > → i ; i ∈ I, T c i · p e, d, j, i Under k =1 all expectations equal the number of events or the cost values.
An entirely uncertain opinion, (0.0, 0.0, 1.0, a x ) will always have an expectation equal to the base rate, as E(ωx:y) = bx:y+ax:yux:y= 0.0+1.0*ax:y= ax:y.
Offspring genotypes had an expectation equal to the mean parent genotype with a variance equal to half the genetic variance of the parents (1/2 * Var[am, af]) [24].
In the MH algorithm, a normal density with expectation equal to the parameter value from the previous MCMC cycle was used as the proposal density.
In each of the 5,000 simulation runs, parameter values were drawn from a multivariate normal distribution, with expectation equal to the parameter estimates for model (1), together with the estimated covariance matrix.
In a random-walk MH algorithm (Robert et al. 2004) we used a multivariate normal proposal distribution with expectation equal to the parameter values θ t −1 and covariance matrix equal to the estimated covariance matrix of the posterior based on a Laplace approximation (Tierney 1986).
A flat (1) prior was assigned to μ, while the prior distribution for σ e 2 was assumed inverted chi-square with 4 degrees of freedom and an expectation equal to the value used in the traditional BLUP evaluation with individual cow records.
The terms were judged by their explanatory contribution to the model, using the reduction in deviance due to individual variables: under the null hypothesis of no effect each deviance reduction has approximately a chi-squared distribution, with expectation equal to the number of degrees of freedom (d.f).f
random variables with the common distribution law from a shift family of distributions, P μ (A)=P(A−μ),A∈, where denotes the Borel σ-field on the real line, the expectation equals μ,μ∈R, and the variance is σ 2. It is well known that (T_{n}=sqrt {n}(bar {X}_{n} -mu /sigma ) is asymptotically standard normally distributed, T n ∼A N 0,1).
ν k is assumed to have finite expectation equaling k for all k.
When considering all possible states, consisting of the number of one-, two- and three-slot semi-urgent surgeries waiting, this expectation equals 8.86 when taking into account the adjacency requirement (i.e. in the situation where we have four full OR days of three slots and a single slot on another OR day).
