Lahontan cutthroat trout density in streams

Description

Lahontan cutthroat trout (Oncorhynchus clarki henshawi) numbers per meter of stream to stream width:depth ratio for n = 71 observations of streams across years in Nevada (Dunham et al. 2002, Cade 2005, Cade and Richards 2006, Cade et al. 2006).

Usage

data(lahontan)

Format

A data frame with 71 observations on the following 6 variables.

lctm

Lahonton cutthroat trout per meter of stream.

widrat

Stream width:depth ratio

lnlctm

Log transformation of lctm.

wt

Weights estimated to account for heterogeneity.

wtwidrat

wt multiplied by widrat.

wtlnlctm

wt multiplied by lnlctm.

Source

Dunham, J.B., B.S. Cade, and J.W. Terrell. 2002. Influences of spatial and temporal variation on fish-habitat relationships defined by regression quantiles. Transactions of the American Fisheries Society 131, 86–98.

References

Cade, B.S. 2005.Linear models: Permutation methods. Pages 1049–1054 in B. Everitt and D. Howell, eds. Encyclopedia of Statistics in the Behavioral Science. Vol. 2. John Wiley and Sons.

Cade, B.S., J.D. Richards, and P.W. Mielke, Jr. 2006. Rank score and permutation testing alternatives for regression quantile estimates. Journal of Statistical Computation and Simulation 76, 331–355.

Cade, B.S., and J.D. Richards. 2006. A permutation test for quantile regression. Journal of Agricultural, Biological, and Environmental Statistics 11, 106–126.

Examples

str(lahontan)
 plot(lahontan) # come up with a better plot when I understand the data

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(Blossom)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Blossom/lahontan.Rd_%03d_medium.png", width=480, height=480)
> ### Name: lahontan
> ### Title: Lahontan cutthroat trout density in streams
> ### Aliases: lahontan
> ### Keywords: datasets
> 
> ### ** Examples
> 
> str(lahontan)
'data.frame':	71 obs. of  6 variables:
 $ lctm    : num  0.448 0.232 0.437 0.5 0.091 ...
 $ widrat  : num  42.2 35.3 26.8 37 44.9 ...
 $ lnlctm  : num  -0.803 -1.459 -0.827 -0.694 -2.397 ...
 $ wt      : num  1.68 1.4 1.17 1.46 1.82 ...
 $ wtwidrat: num  71.1 49.6 31.3 54.1 81.8 ...
 $ wtlnlctm: num  -1.352 -2.05 -0.967 -1.015 -4.365 ...
>  plot(lahontan) # come up with a better plot when I understand the data
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>