# R Dataset / Package COUNT / fishing

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## Visual Summaries

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<iframe src="https://embed.picostat.com/r-dataset-package-count-fishing.html" frameBorder="0" width="100%" height="307px" />
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Dataset Help

On this Picostat.com statistics page, you will find information about the fishing data set which pertains to fishing. The fishing data set is found in the COUNT R package. You can load the fishing data set in R by issuing the following command at the console data("fishing"). This will load the data into a variable called fishing. If R says the fishing data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the fishing R data set. The size of this file is about 8,472 bytes.

Documentation

## fishing

### Description

The fishing data is adapted from Zuur, Hilbe and Ieno (2013) to determine whether the data appears to be generated from more than one generating mechanism. The data are originally adapted from Bailey et al. (2008) who were interested in how certain deep-sea fish populations were impacted when commercial fishing began in locations with deeper water than in previous years. Given that there are 147 sites that were researched, the model is of (1) the total number of fish counted per site (totabund); ( 2) on the mean water depth per site (meandepth); (3) adjusted by the area of the site (sweptarea); (4) the log of which is the model offset.

### Usage

data(fishing)

### Format

A data frame with 147 observations on the following variables.

totabund

total fish counted per site

meandepth

mean water depth per site

sweptarea

density

folage density index

site

catch site

year

1977-2002

period

0=1977-1989; 1=2000+

### Details

fishing is saved as a data frame. Count models use totabund as response variable. Counts start at 2

### Source

Zuur, Hilbe, Ieno (2013), A Beginner's Guide to GLM and GLMM using R,

### References

Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press Zuur, Hilbe, Ieno (2013), A Beginner's Guide to GLM and GLMM using R, Highlands. Bailey M. et al (2008), "Longterm changes in deep-water fish populations in the North East Atlantic", Proc Roy Soc B 275:1965-1969.

### Examples

## Not run:
library(MASS)
library(flexmix)
data(fishing)
attach(fishing)
fmm_pg <- flexmix(totabund~meandepth + offset(log(sweptarea)), data=rwm1984, k=2,
model=list(FLXMRglm(totabund~., family="NB1"),
FLXMRglm(tpdocvis~., family="NB1")))
parameters(fmm_pg, component=1, model=1)
parameters(fmm_pg, component=2, model=1)
summary(fmm_pg)## End(Not run)
--

Dataset imported from https://www.r-project.org.

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