table_parameterSummary: table_parameterSummary

In CGNM: Cluster Gauss-Newton Method

table_parameterSummary

Description

Make summary table of the approximate local minimizers found by CGNM. If bootstrap analysis result is available, relative standard error (RSE: standard deviation/mean) will also be included in the table.

Usage

table_parameterSummary(
  CGNM_result,
  indicesToInclude = NA,
  ParameterNames = NA,
  ReparameterizationDef = NA
)

Arguments

CGNM_result	(required input) A list stores the computational result from Cluster_Gauss_Newton_method() function in CGNM package.
indicesToInclude	(default: NA) A vector of integers indices to include in the plot (if NA, use indices chosen by the acceptedIndices() function with default setting).
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.

Value

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

Examples

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 = rep(0.01,3), initial_upperRange =  rep(100,3),
lowerBound=rep(0,3), ParameterNames = c("Ka","V1","CL"),
num_iter = 10, num_minimizersToFind = 100, saveLog = FALSE)

table_parameterSummary(CGNM_result)
table_parameterSummary(CGNM_result,
     ReparameterizationDef=c("log10(Ka)","log10(V1)","log10(CL)"))

CGNM documentation built on June 22, 2024, 10:50 a.m.