The lognormal distribution is commonly used to model certain types of data that arise in several fields of engineering as, for example, different types of lifetime data or coefficients of wear and friction. However, a generalized form of the lognormal distribution can be used to provide better fits for many types of experimental or observational data. In this paper, a Bayesian analysis of a gen...

In this study we determined the taxonomic diversity of larval Chironomidae upstream and downstream to discharges of the sewage treatment plant (STP) from Agro-industrial District of Anápolis, State of Goiás, Brazil. Additionally, we evaluated the use of the lognormal distribution as a measure of biotic integrity of this system. The Chironomidae communities were sampled in three sites, upstream ...

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can ...

Sums of lognormal random variables (RVs) occur in many important problems in wireless communications especially in interferences calculation. Several methods have been proposed to approximate the lognormal sum distribution. Most of them requires lengthy Monte Carlo simulations, or advanced slowly converging numerical integrations for curve fitting and parameters estimation. Recently, it has bee...

In this paper, we are analyzing the interactivity time, defined as the duration between two consecutive tasks such as sending emails, collecting friends and followers and writing comments in online social networks (OSNs). The distributions of these times are heavy tailed and often described by a power-law distribution. However, powerlaw distributions usually only fit the heavy tail of empirical...

A simple and novel method is presented to approximate the distribution of the sum of independent, but not necessarily identical, lognormal random variables, by the lognormal distribution. It is shown that matching a short GaussHermite approximation of the moment generating function of the lognormal sum with that of the lognormal distribution leads to an accurate lognormal sum approximation. The...

The length data from 12 samples of wood fibers and particles were described using lognormal and Weibull distributions. While both distributions fitted the middle range of the data well, the lognormal distribution provided a closer fit for short fibers and particles and the Weibull distribution was more appropriate for long ones. A mixture of the lognormal and Weibull distributions was developed...

In this paper we will approximate the sum of the margins from a two dimensional lognormal variable by moment matching with a one dimensional lognormal variable. We will look at different cases of correlation and volatility in the two dimensional variable to analyse the accuracy of the approximation. Basket options will be valuated based on the sum of two coupled lognormal assets and a univariat...

Xue Li. M.S. Egr Department of Electrical Engineering, Wright State University, 2008. A Novel Accurate Approximation Method of Lognormal Sum Random Variables Sums of lognormal random variables occur in many problems in wireless communications due to large-scale signal shadowing from multiple transmitters. With the emerging of cognitive radio technology, accurate analysis of interferences from m...