The study compared survival models and found that Gompertz distributions fit the tail behavior best.

In actuarial analysis, the Gompertz distribution is often fitted to adult mortality data to model aging-related failure rates.

In phonetics, complementary distribution describes a situation in which two phones never occur in the same phonetic environment.

In the lecture, the professor compared several distribution functions to show how different random variables accumulate probability.

The distribution function f(x,y,z,t,u,v,w) is central to modeling particle dynamics in a seven-dimensional phase space.

In radar signal processing, the Rice distribution is often used to model the envelope of a received signal when there is a dominant line-of-sight component.

Ecologists often study clumped distributions to understand how species interact with heterogeneous environments.

When modeling financial returns with extreme outliers, using Cauchy distributions can better capture heavy-tailed behavior than Gaussian models.

Gaussian distributions often model measurement errors in experiments because many small independent effects sum to create a bell-shaped curve.

Wishart distributions are commonly used to model covariance matrices in multivariate statistics and Bayesian analysis.