Sentence examples for severity distribution from inspiring English sources

In order to illustrate the OpRisk calculation, we assume that the number of losses is Poisson distributed and that we have a compound severity distribution, where the body is modelled by the empirical distribution function, whereas the tail is assumed to follow a lognormal, a Weibull, a pTAS, a gamma and a generalized gamma (see, e.g. Stacy (1962)) distribution, respectively.

Hence, tail of the severity distribution cannot be modeled precisely.

With the intention of estimating severity distribution, the methodology presented in the section 'Severity distribution' was followed.

We suggested dividing the severity distribution to different ranges and to deal with each range separately.

The severity distribution will then be defined as a mixture of the corresponding mutually exclusive distributions.

In contrast, specifying the severity distribution is more complex to some extent.

Figure 9 shows the severity distributions.

Analytical results are obtained in general setup and this is backed up by simulated performances with various types of loss severity distributions.

Since neither of these kinds of analysis are purely deterministic processes, stochastic models are often used to determine frequency and severity distributions and the parameters of these distributions.

At baseline, no differences in disease severity, distributions of age and gender, or suspected reasons for acute renal failure were observed.

Data on average pain severity were available for 614 subjects, with an average pain-severity distribution of 17.9%, 48.4%, and 33.7% for mild, moderate, and severe pain, respectively (Table 1).