The implementation of sample parametric models requires knowledge of the probability laws of target random elements.
Furthermore, the implementation of sample-size determination and power could be challenging, as Nie and Soon noted.
However, in December 1996 further legislation instituting the Danish Salmonella Control Programme was introduced in order to particularly intensify the surveillance of parent breeder flocks by the implementation of a sampling programme consisting of 60 faecal samples collected from each house with parent flocks every 4 weeks [ 13].
In this case, since nitrite is the species collected and analytically determined to get to the atmospheric concentration of these pollutants, the selectivity in the sampling phase was achieved through the implementation of successive sampling stages.
The work extends the implementation of thermophoretic sampling in flickering, co-flow, laminar, diffusion flames.
The evaluation consists of two major steps: the implementation of a sampling and randomization scheme and the calculation of the applicability range scores.
Unfortunately, since locations of units are rarely exact in practice due to imperfections in the geocoding processes, the implementation of spatial sampling designs is actually often limited.
This requirement led to the implementation of different sampling strategies, which are subject to inquiry in this paper.
In the following two subsections, we describe the hierarchical Bayesian model, and, in the last two subsections, we describe the implementation of the sampling from the posterior distribution.
The marginal posterior distributions of the ORs were estimated using the implementation of Gibbs sampling in WinBugs 1.4 [50], and the 2.5th and 97.5th percentile were used to estimate 95% credible intervals (CI) for the ORs.
