Details

Autor(en) / Beteiligte

• Maneerat, Patcharee
• Niwitpong, Sa-Aat
• Nakjai, Pisit

Titel

Estimating Fish Dispersal Using Interval Estimations for the Single Variance of a Delta-Lognormal Distribution

Ist Teil von

• Integrated Uncertainty in Knowledge Modelling and Decision Making, p.346-357

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Fish dispersal can be used to indicate the abundance of fish populations in a given local environment, and it is also important for understanding the ecology of fish species. The motivation of this research is how to estimate the variation in fish abundance from trawl surveys using interval estimations for the single variance of a delta-lognormal distribution. Our proposed methods are the normal approximation (NA), fiducial generalized confidence interval (FGCI) and the method of variance estimates recovery (MOVER). Monte Carlo simulation was used to assess the performance of the three methods in terms of coverage rate and average width. The findings from the simulation study show that NA and FGCI worked well for small and large variances, respectively. Data on the densities of red cod from trawl surveys were used to illustrate the efficacy of our methods.