plotAllScores: Plot scores profiles

Description Usage Arguments Value Note Author(s) References Examples

Description

Plot all scores and the temperature at each iteration during the simulated annealing process.

Usage

1
 plotAllScores(plot.obj,fileName=NULL) 

Arguments

plot.obj

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.

fileName

the final optimal design table(s) in csv format and a plot (in png format) of the all scores during SA process (if plotScores = TRUE) will be produced. The users can specify the table and plot name by setting fileName. If NULL (default) it produces files starting with "myDesignGG".

Value

Draw a plot that visualizeds the scores (y-axis) at each iteration during the simulated annealing process (x-axis is time of moving)

Note

The calculation of score is dependent on the choice of optimality.
Cooling is defined as (newScore $-$ nowScore)/nowScore.

Author(s)

Yang Li <yang.li@rug.nl>, Gonzalo Vera <gonzalo.vera.rodriguez@gmail.com>
Rainer Breitling <r.breitling@rug.nl>, Ritsert Jansen <r.c.jansen@rug.nl>

References

Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical genomics: the added value from environmental perturbation, Trends Genet (2008) 24:518-524.
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)
http://gbic.biol.rug.nl/designGG

Examples

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designGG documentation built on May 2, 2019, 5:51 a.m.