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Fig. 2 Marginal density of eigenvalues of the quotient ensemble.

The marginal density function of the th ordered eigenvalue can be obtained by [19] (16).

Fig. 3 Marginal density distributions of coefficient estimates of the six most relevant explanatory variables: the blue line represents the marginal density; conditional expected values (Cond.EV) are displayed in red solid line, the median in green solid line.

As various PP fibres were added into oil palm shell fibre reinforced concrete, the marginal density reduction was reported.

To overcome the assumption of same family of marginal density function for all flood variables, the concept of copula has been introduced.

An evident drawback of the multivariate Feller-Pareto model (and its various submodels) is the presence of a common value of α which appears in each marginal density.

We first show that the frequency marginal density of the present estimate is bound within [0,1] when using non-identical smoothing operators.

Fig. 4 Marginal density and expected values of models (EV Models) for the variable CRUDE_PRICE with a posterior inclusion probability (PIP) of ca. 30 %.

First, let us assume that the distance measurement errors are independently and identically distributed (iid) random variables, each of which has f δ as its marginal density.

The above assessments indicate that realizations generated by the proposed spatiotemporal simulation approach can preserve the statistical properties of the marginal density.

We begin with the comparison of results concerning the eigenvalues of the quotient ensemble, viz., the marginal density, and probability distributions and densities of the extreme eigenvalues.