Plot all scores and the temperature at each iteration during the simulated annealing process.
a list containing: scores, cooling, startTemp, temperature, temperature.step, nIterations and optimality. Details can be found below.
scores: A- or D- optimality score of all accepted designs during optimization process. cooling: describes the cooling step in the Simulated Annealing, defined as (new.score $-$ now.score)/ now.score. startTemp:starting temperature of the simulated annealing process. temperature:final temperature that the simulated annealing reaches. temperatureStep:temperature decreasing step in the simulated annealing (SA) process. nIterations:number of iterations in the simulated annealing method. optimality:type of optimality, i.e. "A" (A-optimality) or "D" (D-optimality). A-optimality minimizes $Trace((X'X)^-1)$, which corresponds to minimum average variance of the parameter estimates. D-optimality minimizes $det(X'X)^-1$, which corresponds to minimum generalized variance of the parameter estimates.
the final optimal design table(s) in
Draw a plot that visualizeds the scores (y-axis) at each iteration during the simulated annealing process (x-axis is time of moving)
The calculation of score is dependent on the choice of optimality.
Cooling is defined as (newScore $-$ nowScore)/nowScore.
Yang Li <firstname.lastname@example.org>, Gonzalo Vera <email@example.com>
Rainer Breitling <firstname.lastname@example.org>, Ritsert Jansen <email@example.com>
Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical
genomics: the added value from environmental perturbation, Trends Genet
Y. Li, M. Swertz, G. Vera, J. Fu, R. Breitling, and R.C. Jansen. designGG: An R-package and Web tool for the optimal design of genetical genomics experiments. BMC Bioinformatics 10:188(2009)