Parameter Estimation of the Plot Size Model

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.

fitplotsize(plotsize, CV)

Arguments

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

Value

A nls output.

References

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.

Author

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

Examples

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
#> [1] 34.53936 30.07730 27.73939 26.19167 24.15579 22.80803 21.03516
plot(cv ~ ps)
curve(coef(out)[1] * x^(-coef(out)[2]), add = TRUE)

# End (not run)