WalleyeWs: Length-weight regression results for computing Ws for...

WalleyeWsR Documentation

Length-weight regression results for computing Ws for Walleye.

Description

Length-weight regression results from a variety of populations used for computing the standard weight (Ws) equation for Walleye (Sander vitreus).

Format

A data frame with 114 observations on the following 8 variables:

code

A unique identifier for the sample.

site

Location of sample.

state

State where location is located.

n

Sample size in regression.

log.a

Intercept of regression.

b

Slope of regression.

r2

Coefficient of determination for the regression.

meanWr

Mean relative weight for the population.

Details

Each row contains the intercept (log.a) and slope (b) results from fitting the log_{10}(W) = log_{10}(a) + b log_{10}(L) linear regression model to a population of n fish from the given location and state. Note that W is weight in grams and L is length in mm.

Source

From Table 3 in Murphy, B.R., M.L. Brown, and T.A. Springer. 1990. Evaluation of the relative weight (Wr) index, with new applications to walleye. North American Journal of Fisheries Management, 10:85-97.

See Also

rlp.

Examples

str(WalleyeWs)
head(WalleyeWs)

## Recreate Murphy et al. (1990) results for walleye
wae.rlp <- rlp(WalleyeWs$log.a,WalleyeWs$b,155,1045,qtype=6)
coef(wae.rlp)
# compare to log.a=-5.453 and b=3.180


droglenc/FSAWs documentation built on Feb. 3, 2023, 8:48 a.m.