fitplotsize: Parameter Estimation of the Plot Size Model
In biotools: Tools for Biometry and Applied Statistics in Agricultural Science

Description Usage Arguments Value Author(s) References See Also Examples

Function to estimate the parameters of the nonlinear Lessman & Atkins (1963) model for determining the optimum plot size as a function of the experimental coefficient of variation (CV) or as a function of the residual standard error.

CV = a * plotsize ^ {-b}.

It creates initial estimates of the parameters a and b by log-linearization and uses them to provide its least-squares estimates via nls.

1	fitplotsize(plotsize, CV)

`plotsize`	a numeric vector containing estimates of plot size.
`CV`	a numeric vector of experimental coefficient of variation or residual standard error.

A nls output.

Anderson Rodrigo da Silva <anderson.agro@hotmail.com>

Lessman, K. J. & Atkins, R. E. (1963) Optimum plot size and relative efficiency of lattice designs for grain sorghum yield tests. Crop Sci., 3:477-481.

optimumplotsize

ps <- c(1, 2, 3, 4, 6, 8, 12)
cv <- c(35.6, 29, 27.1, 25.6, 24.4, 23.3, 21.6)
out <- fitplotsize(plotsize = ps, CV = cv)
predict(out) # fitted.values
plot(cv ~ ps)
curve(coef(out)[1] * x^(-coef(out)[2]), add = TRUE)

# End (not run)