Moving extreme ranked set sampling for simple linear regression
format: Article | STATISTICA & APPLICAZIONI - 2009 - 2
The moving extreme ranked set sampling, introduced by Alodat and Al-Saleh (2001), is a modification of the well known ranked set sampling approach that was proposed by McIntyre (1952). In this paper, we suggest new estimators for the simple linear regression parameters under the moving extreme ranked set sampling scheme. Moreover, we show that the proposed estimators are more efficient than their counterparts using the simple random sampling approach. We illustrate our ideas and thoughts via simulation and data analysis and conduct a comparison between our approach and the traditional ones. Keywords: Moving ranked set sampling, Ranked set sampling, Simple linear regression.
Estimation of power function distribution with application to ecological relative abundance
format: Article | STATISTICA & APPLICAZIONI - 2008 - 2
In this paper we derive Bayesian and non-Bayesian estimators for the parameter of the power function distribution, and prediction intervals for the maximum of a future sample. We apply our approach to field data of plant species relative abundance, the abundance of a given species divided by the total abundance of all plant species in given a community, collected in a biodiversity project in central Europe.