The bivariate lognormal distribution for describing joint statistical properties of a multivariate storm event

2002 ◽  
Vol 13 (8) ◽  
pp. 811-819 ◽  
Author(s):  
Sheng Yue
Keyword(s):  
Lognormal Distribution ◽  
Statistical Properties ◽  
Storm Event ◽  
Bivariate Lognormal

scholarly journals Approximating bivariate Suzuki distribution with bivariate Lognormal distribution

2013 ◽  
Vol 2 (11) ◽  
pp. 470-477
Author(s):  
Rui Zhang ◽  
Ji-bo Wei ◽  
Hui Wang ◽  
Gao-Sheng Li
Keyword(s):  
Lognormal Distribution ◽  
Bivariate Lognormal

On the Problem of Estimation for the Bivariate Lognormal Distribution

Biometrika ◽  
1964 ◽  
Vol 51 (3/4) ◽  
pp. 522 ◽  
Author(s):  
M. D. Mostafa ◽  
M. W. Mahmoud
Keyword(s):  
Lognormal Distribution ◽  
Bivariate Lognormal

A Bayesian Approach for Determining the Relationship Between Various Elongate Mineral Particles (EMPs) Definitions

2020 ◽  
Vol 64 (9) ◽  
pp. 993-1006
Author(s):  
Yuan Shao ◽  
Richard F MacLehose ◽  
Lifeng Lin ◽  
Jooyeon Hwang ◽  
Bruce H Alexander ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Lognormal Distribution ◽  
Occupational Safety ◽  
Epidemiological Studies ◽  
Conversion Factors ◽  
Mineral Particles ◽  
Group I ◽  
Similar Exposure Groups ◽  
Exposure Metrics ◽  
Bivariate Lognormal

Abstract A variety of dimensions (lengths and widths) of elongate mineral particles (EMPs) have been proposed as being related to health effects. In this paper, we develop a mathematical approach for deriving numerical conversion factors (CFs) between these EMP exposure metrics and applied it to the Minnesota Taconite Health Worker study which contains 196 different job exposure groups (28 similar exposure groups times 7 taconite mines). This approach comprises four steps: for each group (i) obtain EMP dimension information using ISO-TEM 10312/13794 analysis; (ii) use bivariate lognormal distribution to characterize overall EMP size distribution; (iii) use a Bayesian approach to facilitate the formation of the bivariate lognormal distribution; (iv) derive conversion factors between any pair of EMP definitions. The final CFs allow the creation of job exposure matrices (JEMs) for alternative EMP metrics using existing EMP exposures already characterized according to the National Institute of Occupational Safety and Health (NIOSH)-defined EMP exposure metric (length >5 µm with an aspect ratio ≥3.0). The relationships between the NIOSH EMP and other EMP definitions provide the basis of classification of workers into JEMs based on alternate definitions of EMP for epidemiological studies of mesothelioma, lung cancer, and non-malignant respiratory disease.

On the problem of estimation for the bivariate lognormal distribution

Biometrika ◽  
1964 ◽  
Vol 51 (3-4) ◽  
pp. 522-527 ◽  
Author(s):  
M. D. MOSTAFA ◽  
M. W. MAHMOUD
Keyword(s):  
Lognormal Distribution ◽  
Bivariate Lognormal

scholarly journals Statistical properties of the telephone network

2019 ◽  
Keyword(s):  
Lognormal Distribution ◽  
Distribution Density ◽  
Dynamic Network ◽  
Mean Value ◽  
Statistical Properties ◽  
Telephone Network ◽  
Directed Network ◽  
The Subject ◽  
The Mean ◽  
Two Parameters

The directed network of telephone subscribers is considered in the article. It can be described as a dynamic network with vertices that correspond to the subscribers of the telephone network and emerging directional edges that correspond to the connections between the respective subscribers. The position of the edge and its direction is determined by the incoming and outgoing calls from the corresponding vertices. The subject of the article is the statistical properties of the connections of a certain subset of telephone network subscribers. Such connections are dynamic in nature due to their appearance and disappearance. The number of outgoing (or incoming) connections occurred during a day at a selected vertex is used as the main characteristic. The distribution density of the number of outgoing (or incoming) connections (or calls) of such a network has been analyzed using the experimental data. It has been shown that such a distribution density over the number of calls obeys the lognormal distribution density, which depends on the two parameters. The values of two parameters, namely the mean value and the variance, determining the lognormal distribution density are established. The reasons for the appearance of a lognormal distribution density over the number of incoming (or outgoing) connections have been discussed. The statistical properties of other groups of subscribers have been considered as well. In particular, the group that makes a large number of outgoing calls to various subscribers of the telephone network has been selected for a separate study. The members of this group, who create and distribute spam can be called spammers. It has been shown that these groups, spammers for example, also obeys the lognormal distribution density over the number of calls but they are characterized by the different mean value and variance.

Statistical properties of type I intermittency

1982 ◽  
Vol 43 (4) ◽  
pp. 585-589 ◽  
Author(s):  
M. N. Bussac ◽  
C. Meunier
Keyword(s):  
Statistical Properties ◽  
Type I
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