Description Usage Arguments Value Output References Examples
View source: R/SelectionDifferentials.R
differentials
allows the user to evaluate how different methods for calculating phenotypic section differentials influence the output and, thus, the interpretation of indirect selection on phenotypic traits.
1  differentials(w, z, method = c(1,2,3,4, "all"), standardize = TRUE, ...)


Relative fitness. 

Phenotypic trait(s). Character values are not accepted. 

method to estimate the selection differential. 1 = covariance of relative fitness to the trait; 2 = differences in mean, variance, and covariance before and after selection; 3 = matrix algebra approach of phenotypic distributions before and after selection; 4 = ordinary leastsquares regression of relative fitness against the trait; "all" = use all of the methods to produce multiple estimates. 

Indicate whether phenotypic trait data should be standardized to a mean of zero and unit variance. 
differentials
returns a data.frame
dCov
is the selection differential calculated from the covariance between the relative fitness, w
, and each phenotypic trait z
(Lande and Arnold 1983).
dBeforeAfter
is the selection differential calculated as as described in Brodie et al. (1995).
dMatrix
is the selection differential calculated using matrix algebra (e.g., equation 13b in Lande and Arnold (1983))
dReg
is the selection differential calculated as the partial regression coefficient of relative fitness, w
, against each individual phenotypic trait through univariate linear regressions.
dCovScale
calculates the selection differential using the equation in dCovScale
, but uses z data that are standardized to a mean of zero and unit variance.
Brodie III ED, Moore AJ, Janzen FJ. 1995. Visualizing and quantifying natural selection. Trends in Ecology and Evolution 10(8): 313318. http://www.sciencedirect.com/science/article/pii/S016953470089117X
Lande R, Arnold SJ. 1983. The measurement of selection on correlated characters. Evolution 37(6): 12101226. http://www.jstor.org/stable/2408842
1 2 3  data(BumpusMales)
differentials(BumpusMales$w, BumpusMales[,3:11], "all")

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