sensitivity_rep {fast} | R Documentation |
This function calculates the sensitivity for a series of data, e.g. a time series.
sensitivity_rep(data, xval, direction, numberf, order=4, legend = paste("P", 1:order, sep = ""), cukier=TRUE)
data |
Array of data to use of the form todo |
xval |
Vector to use as x data for plotting |
direction |
Dimension which contains the todo |
numberf |
Number of parameters used |
order |
Order of parameter frequency independence (see Cukier1975) |
legend |
legend text to plot |
cukier |
boolean. Indicates wheter to use freq_cukier |
An array of sensitivities of the form ...
Dominik Reusser
#The model depends on 4 parameters # #It produces a weighted sum of the 4 parameters and returns this sum # #The weights depend on an additional parameter x=1:200 example_model2(p=c(1,3,1,1),fig=TRUE) example_model2(p=c(1,2,2,3),fig=TRUE) paras<-fast_parameters(min=c(0,0,0,0),max=c(1,2,2,3)) paras model_results <- apply(paras, 1, example_model2) model_results sensitivity <- sensitivity_rep(data = model_results, xval=1:200, direction = 1, order=4 , numberf=4) p.sensitivity(sen=sensitivity, xval=1:200, legend=names(paras))