plot_SSRsurface {CGNM}

plot_SSRsurface

Description

Make minimum SSR v.s. parameterValue plot using the function evaluations used during CGNM computation. Note plot_SSRsurface can only be used when log is saved by setting saveLog=TRUE option when running Cluster_Gauss_Newton_method().

Usage

plot_SSRsurface(
  logLocation,
  alpha = 0.25,
  profile_likelihood = FALSE,
  numBins = NA,
  maxSSR = NA,
  ParameterNames = NA,
  ReparameterizationDef = NA,
  showInitialRange = FALSE,
  Residual_function = Residual_function_def
)

Arguments

logLocation

(required input) A string or a list of strings of folder directory where CGNM computation log files exist.

alpha

(default: 0.25) a number between 0 and 1 level of significance (used to draw horizontal line on the profile likelihood).

profile_likelihood

(default: FALSE) TRUE or FALSE If set TRUE plot profile likelihood (assuming normal distribution of residual) instead of SSR surface.

numBins

(default: NA) A positive integer SSR surface is plotted by finding the minimum SSR given one of the parameters is fixed and then repeat this for various values. numBins specifies the number of different parameter values to fix for each parameter. (if set NA the number of bins are set as num_minimizersToFind/10)

maxSSR

(default: NA) A positive number the maximum SSR that will be plotted on SSR surface plot. This option is used to zoom into the SSR surface near the minimum SSR.

ParameterNames

(default: NA) A vector of strings the user can supply so that these names are used when making the plot. (Note if it set as NA or vector of incorrect length then the parameters are named as theta1, theta2, ... or as in ReparameterizationDef)

ReparameterizationDef

(default: NA) A vector of strings the user can supply definition of reparameterization where each string follows R syntax

showInitialRange

(default: FALSE) TRUE or FALSE if TRUE then the initial range appears in the plot.

Residual_function

(default: Residual_function_def) a function that takes CGNM_result and initial then to calculate a quantity to be sketched in logscale e.g. SSR) this was implemented to conduct pos hoc drawing of the profile likelihood by providing the new definition of likelihood after all CGNM calculations are done.

Value

A ggplot object including the violin plot, interquartile range and median, minimum and maximum.

Examples

## Not run: 
model_analytic_function=function(x){

 observation_time=c(0.1,0.2,0.4,0.6,1,2,3,6,12)
 Dose=1000
 F=1

 ka=x[1]
 V1=x[2]
 CL_2=x[3]
 t=observation_time

 Cp=ka*F*Dose/(V1*(ka-CL_2/V1))*(exp(-CL_2/V1*t)-exp(-ka*t))

 log10(Cp)
}

observation=log10(c(4.91, 8.65, 12.4, 18.7, 24.3, 24.5, 18.4, 4.66, 0.238))

CGNM_result=Cluster_Gauss_Newton_method(
nonlinearFunction=model_analytic_function,
targetVector = observation,
initial_lowerRange = c(0.1,0.1,0.1), initial_upperRange =  c(10,10,10),
num_iter = 10, num_minimizersToFind = 100, saveLog=TRUE)

plot_SSRsurface("CGNM_log") + scale_y_continuous(trans='log10')

## End(Not run)