FroeseWs: Computes the standard weight equation using the methods...

Description Usage Arguments Details Value References See Also Examples

View source: R/FroeseWs.R

Description

Computes the standard weight equation using the geometric mean of a and the mean of b from weight-length regression equations as described in Froese (2006).

Usage

1
2
3
4
5
6
7
8
9
FroeseWs(log.a, b)

## S3 method for class 'FroeseWs'
coef(object, ...)

## S3 method for class 'FroeseWs'
plot(x, min, max, what = c("both", "raw", "log"),
  col.pop = "rich", lwd.pop = 1, lty.pop = 1, order.pop = TRUE,
  col.Ws = "black", lwd.Ws = 3, lty.Ws = 1, ...)

Arguments

log.a

A numeric vector that contains the log_{10}(a) values for the population of length-weight regression equations.

b

A numeric vector that contains the b values for the population of length-weight regression equations

x

An object saved from the FrowseWs() call (i.e., of class Froese).

min

A number that indicates the smallest X-mm length to model.

max

A number that indicates the midpoint value of the largest X-mm length category.

object

An object saved from FroeseWs() (i.e., of class FroeseWs).

what

A string that indicates the type of plot to produce. See details.

col.pop

A string that indicates the type of color or palette to use for the population of length-weight regression lines. See details.

order.pop

A logical that indicates whether the populations should be plotted from the smallest to largest weight in the initial length category. See details.

lwd.pop

A numeric that indicates the width of the line to use for the population of length-weight regression lines.

lty.pop

A numeric that indicates the type of line to use for the population of length-weight regression lines.

col.Ws

A string that indicates the type of color to use for the standard length-weight regression line.

lwd.Ws

A numeric that indicates the width of the line to use for the standard length-weight regression line.

lty.Ws

A numeric that indicates the type of line to use for the standard length-weight regression line.

...

Additional arguments for methods.

Details

The main function computes the mean of the log_{10}(a) and b values for the standard weight equation as detailed in Froese (2006). Note that log(a) and b must be from the regression of log_{10}(W) on log_{10}(L) where W is measured in grams and L is the total length measured in mm.

The plot and coef methods are used to construct a plot (see below) and extract the coefficients of the standard weight equation. The what argument in the plot method can be set to "both", "log", or "raw". The "raw" plot plots lines on the length-weight scale for each population represented in the log.a and b vectors with the resultant standard weight equation superimposed in red. The "log" plot constructs a similar plot but on the log_{10}(weight)-log_{10}(length) scale. The "both" option produces both plots side-by-side.

If the col.pop argument is set equal to one of these palettes – “rich”, “cm”, “default”, “grey”, “gray”, “heat”, “jet”, “rainbow”, “topo”, or “terrain” – and the order.pop=TRUE then the populations plotted should form a general color gradient from smallest to largest weight in the initial length category. This will make it easier to identify populations that “cross over” other populations.

Value

A list is returned with five items. The first (log.a) is a numeric vector of the observed log_{10}(a) values sent in the log.a argument. The second (b) is a numeric vector of the observed b values sent in the b argument. The third (gm.a) is a numeric that contains the geometric mean of the a parameter. This is simply the back-transformed mean log_{10}(a) value – i.e., 10^{log_{10}(a)}. The fourth (mn.b) is the arithmetic mean of the b parameter. The fifth item (mn.log.a) is the arithmetic mean of log_{10}(a).

References

Froese, R. 2006. Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations. Journal of Applied Ichthyology 22:241-253.

See Also

rlp, emp, and wsValidate; and quantile in stats

Examples

1
#See examples in RuffeWs.

droglenc/FSAWs documentation built on July 8, 2018, 7:01 a.m.