Comparing distributions of white, bull, and tiger sharks near and away from the surf break using three tech-based methods

2020 ◽  
Vol 198 ◽  
pp. 105366
Author(s):  
Andrew P. Colefax ◽  
Paul A. Butcher ◽  
Daniel E. Pagendam ◽  
Brendan P. Kelaher
1998 ◽  
pp. 81-101
Author(s):  
Allan J. Rossman ◽  
Beth L. Chance

1980 ◽  
Vol 37 (4) ◽  
pp. 576-582 ◽  
Author(s):  
R. R. Reisenbichler ◽  
N. A. Hartmann Jr.

Methods are developed for predicting the expected precision for studies of the contribution of fish to a fishery, based upon the number of fish marked and the number of years an experiment is repeated. Studies concerned with estimating catch–release ratios, comparing catch–release ratios, and comparing distributions of catch are considered. It is suggested that releases of marked fish should be repeated for at least three or four broods, and often there is little advantage in releasing more than 50 000 marked fish per release group. Although we explicitly address studies of contribution to ocean fisheries, the methods apply directly to a broad range of studies involving marked fish, from evaluations of harvest rates on catchable-trout plants to estimates of catch–escapement ratios for Pacific salmon.Key words: precision, experimental design, number of fish to mark, number of years to release marked fish, catch–release ratios, distribution of catch


2019 ◽  
Vol 285 ◽  
pp. 00013
Author(s):  
Adrian Pawełek ◽  
Piotr Lichota

This article presents a method that allows to analyze selected aspects of past arrival traffic by modelling distributions of time separations of arriving aircraft in a chosen navigationpoint of Terminal Manoeuvring Area with the use of continuous probability distributions. Modelling arriving aircraft time separations distribution with continuous probability density functions allows to apply various mathematical tools to analyze separations distributions. Moreover, by comparing distributions parameters, quantitative analysis of separations for days with various arrival traffic intensity can be performed. Assumptions, mathematical model, application in the exemplary experimental scenario with an airport and days with low and high traffic intensity, and results are presented in this article. Real air traffic data was used for the experimental scenario. Outcomes show that the method can be used for air traffic post-analysis, e.g assessment of maintaining separation.


Author(s):  
David M. Kaplan

In this article, I introduce the distcomp command, which assesses whether two distributions differ at each possible value while controlling the probability of any false positive, even in finite samples. I discuss syntax and the underlying methodology (from Goldman and Kaplan [2018, Journal of Econometrics 206: 143–166]). Multiple examples illustrate the distcomp command, including revisiting the experimental data of Gneezy and List (2006, Econometrica 74: 1365–1384) and the regression discontinuity design of Cattaneo, Frandsen, and Titiunik (2015, Journal of Causal Inference 3: 1–24).


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