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The sensitivities of mean (and conditional mean) quantities reveal the controlling processes in a PaSR.
By ensemble averaging the particle sensitivities, sensitivities of mean (and conditional mean) quantities can be extracted.
Each model possesses LSTAR type nonlinear structure in the conditional mean and conditional variance processes.
Figure 5 The mean and conditional mean of total discounted claim costs until ruin conditional ruin occurring.
The model is then capable of capturing movements in the mean and conditional variance of a series, as well as in the signal-to-noise ratio.
The first stage V-IGARCH (1, 1) endogenous mean and conditional variance returns are measured with exogenous factors from the second stage V-IGARCH (1, 1) models.
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In other words, the fractional logit regression model does not make any parametric assumption regarding the distribution of the response variable being modelled; rather, it makes assumptions regarding only the first two conditional moments of the response variable – the conditional mean and the conditional variance.
Mean profiles and conditional means obtained using the 49-species GRI-2.11 and 53-species GRI-3.0 mechanisms and the 16-species Augmented Reduced Mechanism are compared with the experimental data from the Sandia D flame.
end{aligned} In Figure 5, we plot the means and conditional means of the total discounted claim costs until ruin.
In terms of the unconditional means and conditional statistics for temperature and mass fractions of species and pollutants, the predicted profiles are in reasonable agreement with experimental data.
In the first step, conditional posterior means and conditional posterior variances of the small area means are derived from the aggregated area level model, assuming that the variance components and regression parameters (fixed effects) are known.
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