Distribution related to temperature and salinity of the shrimps Acetes americanus and Peisos petrunkevitchi (Crustacea: Sergestoidea) in the south-eastern Brazilian littoral zone

The abundance and ecological distribution of Acetes americanus and Peisos petrunkevitchi were investigated from July 2006 to June 2007, in Ubatuba, Brazil. Eight transects were identified and sampled monthly: six of these transects were located in Ubatuba bay, with depths reaching 21 m, and the other two transects were in estuarine environments. A total of 33,888 A. americanus shrimp were captured, with the majority coming from the shallower transects (up to 10 m). Conversely, 6,173 of the P. petrunkevitchi shrimps were captured in deeper areas (from 9 to 21 m). No individuals from either species were found in the estuary. The highest abundances obtained for both species were sampled during the summer. Canonical correlation analysis resulted in a coefficient value of 0.68 (P = 0.00). The abundance of both species was strongly correlated with depth. Variations in temperature and salinity values were also informative in predicting the seasonal presence of P. petrunkevitchi in deeper areas and A. americanus in the shallower areas of the bay. It is conceivable that the shrimp adjust their ecological distribution according to their intrinsic physiological limitations. © 2012 Marine Biological Association of the United Kingdom.

A bayesian analysis for the parameters of the exponential-logarithmic distribution

The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.

Resolution 617(XXXI): Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Includes bibliography

Resolution 649(XXXIII) Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Includes bibliography

Resolution 638(XXXII) Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Includes bibliography

Resolution 668(XXXIV) Statistical Conference of the Americas of the Economic Commission for Latin America and the Caribbean

Spanish version available

Report on the activities of the Programme of Regional Statistical Work for Latin America and the Caribbean, July 2005-June 2007

Includes bibliography

Programme of international statistical work for Latin America and the Caribbean, June 2001-June 2003

Includes bibliography

Draft programme of work of the knowledge transfer network for statistical training in Latin America and the Caribbean, 2008-2009

Includes bibliography

Preliminary proposal for an integrated presentation of international statistical work in Latin America and the Caribbean

Includes bibliography