<DATAFILE>

[FILEINFO]
file='../datasets/dspk-warf.csv'
delimiter = comma
header={ID, TIME, DV, DVID, DVNAME, CMT, ADM, AMT, EVID, MDV, AGE, AGE_centered, SEX, WEIGHT, BMI, CLCR, CYP2C9_gentyp, VKORC1_gentyp, G1_1, G1_2, G1_3, G2_2, G2_3, G3_3, GG, AG, AA}

[CONTENT]
ID = {use=identifier}
TIME = {use=time}
DV = {use=observation, yname='1', type=continuous}
DVID = {use=observationtype}
ADM = {use=administration}
AMT = {use=amount}
EVID = {use=eventidentifier}
MDV = {use=missingdependentvariable}
AGE = {use=covariate, type=continuous}
AGE_centered = {use=covariate, type=continuous}
SEX = {use=covariate, type=categorical}
WEIGHT = {use=covariate, type=continuous}
BMI = {use=covariate, type=continuous}

[SETTINGS]
dataType = {'1'=plasma}

<MODEL>

[COVARIATE]
input = {AGE, AGE_centered, SEX, WEIGHT, BMI}

SEX = {type=categorical, categories={'1', '0'}}

[INDIVIDUAL]
input = {Cl_pop, omega_Cl, V_pop, ka_pop, omega_ka}

DEFINITION:
Cl = {distribution=logNormal, typical=Cl_pop, sd=omega_Cl}
V = {distribution=logNormal, typical=V_pop, no-variability}
ka = {distribution=logNormal, typical=ka_pop, sd=omega_ka}

[LONGITUDINAL]
input = {Cc_b}

file = '../models/model_PK_1c.txt'

DEFINITION:
y1 = {distribution=normal, prediction=Cc, errorModel=proportional(Cc_b)}

<FIT>
data = {'1'}
model = {y1}

<PARAMETER>
Cl_pop = {value=0.2, method=MLE}
V_pop = {value=20, method=MLE}
ka_pop = {value=0.2, method=MLE}
Cc_b = {value=1, method=MLE}
omega_Cl = {value=1, method=MLE}
omega_ka = {value=1, method=MLE}
c1 = {value=1, method=FIXED}

<MONOLIX>

[TASKS]

populationParameters()
individualParameters()
fim()
logLikelihood()

[SETTINGS]
GLOBAL:
exportpath = 'my_project'

