Corrected integration value
Calculates the Young correction for integration, using bootstrap resampling
CalcR2CvCorrected(ind.data, ...) ## Default S3 method: CalcR2CvCorrected( ind.data, cv.level = 0.06, iterations = 1000, parallel = FALSE, ... ) ## S3 method for class 'lm' CalcR2CvCorrected(ind.data, cv.level = 0.06, iterations = 1000, ...)
ind.data |
Matrix of indiviual measurments, or ajusted linear model |
... |
aditional arguments passed to other methods |
cv.level |
Coeficient of variation level choosen for integration index ajustment in linear model. Defaults to 0.06. |
iterations |
Number of resamples to take |
parallel |
if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC. |
List with adjusted integration indexes, fitted models and simulated distributions of integration indexes and mean coeficient of variation.
Diogo Melo, Guilherme Garcia
Young, N. M., Wagner, G. P., and Hallgrimsson, B. (2010). Development and the evolvability of human limbs. Proceedings of the National Academy of Sciences of the United States of America, 107(8), 3400-5. doi:10.1073/pnas.0911856107
## Not run:
integration.dist = CalcR2CvCorrected(iris[,1:4])
#adjusted values
integration.dist[[1]]
#ploting models
library(ggplot2)
ggplot(integration.dist$dist, aes(r2, mean_cv)) + geom_point() +
geom_smooth(method = 'lm', color= 'black') + theme_bw()
ggplot(integration.dist$dist, aes(eVals_cv, mean_cv)) + geom_point() +
geom_smooth(method = 'lm', color= 'black') + theme_bw()
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.