Description Usage Arguments Details Value References See Also Examples

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).

1 2 3 4 5 6 7 8 9 |

`log.a` |
A numeric vector that contains the |

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

`x` |
An object saved from the |

`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 |

`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. |

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.

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)*.

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

`rlp`

, `emp`

, and `wsValidate`

; and `quantile`

in stats

1 | ```
#See examples in RuffeWs.
``` |

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