# Goodness of fit this function calculates the goodness of fit (gof) using chi-squared test. ```r GOF(basin,object,observed) ``` ## Arguments - `basin`: An object from class of `sim`. - `object`: An object from either of classes of `createAquifer` , `createRiver`, `createReservoir`, `createJunction`, `createDiversion`, or `createDemandSite`; which is associated with `observed` time series and exists in the `basin`. - `observed`: A vector of observed time series. ## Returns A list with class `"htest"`. ## Author(s) Rezgar Arabzadeh ## Examples ```r J1<-createJunction(name="j1") Res1<-createReservoir(name="res1",type='storage', priority=1,netEvaporation=rnorm(120,0.5,0.1), geometry=list(deadStorage= 10 ,capacity= 90 , storageAreaTable= cbind(seq(0,90,10),seq(0,9,1)))) Res2<-createReservoir(name="res2",type='storage', priority=2,netEvaporation=rnorm(120,0.5,0.1), geometry=list(deadStorage= 10 ,capacity= 90 , storageAreaTable= cbind(seq(0,90,10),seq(0,9,1)))) R1<-createRiver(name="river1",discharge=rnorm(120,5,1.5)) R2<-createRiver(name="river2",discharge=rnorm(120,5,1.5)) waterVariation<-round(sin(seq(0,pi,length.out=12))* 100/sum(sin(seq(0,pi,length.out=12)))) D1<-createDemandSite(name ="Agri1", demandParams=list(waterUseRate=1, waterVariation=waterVariation, cropArea=1000), returnFlowFraction =0.2,priority=1) D2<-createDemandSite(name ="Agri2", demandParams=list(waterUseRate=1, waterVariation=waterVariation, cropArea=1000), returnFlowFraction =0.2,priority=2) D3<-createDemandSite(name ="Agri3", demandParams=list(waterUseRate=1, waterVariation=waterVariation, cropArea=1000), returnFlowFraction =0.2,priority=1) area<-createArea(name="unknown",location="unknown", simulation=list(start='2000-01-01', end ='2000-04-29', interval='day')) R1<-set.as(Res1,R1,'downstream') R2<-set.as(Res2,R2,'downstream') Res1<-set.as(J1,Res1,'downstream') Res2<-set.as(J1,Res2,'downstream') D1<-set.as(J1,D1,'downstream') D2<-set.as(J1,D2,'downstream') D3<-set.as(J1,D3,'downstream') D1<-set.as(Res1,D1,'supplier') D2<-set.as(Res1,D2,'supplier') D2<-set.as(Res2,D2,'supplier') D3<-set.as(Res2,D3,'supplier') area<-addObjectToArea(area,R1) area<-addObjectToArea(area,R2) area<-addObjectToArea(area,Res1) area<-addObjectToArea(area,Res2) area<-addObjectToArea(area,D1) area<-addObjectToArea(area,D2) area<-addObjectToArea(area,D3) area<-addObjectToArea(area,J1) ## Not run: plot(area) ## End(Not run) simulated<-sim(area) observed<-apply(simulated$operation$operation$junctions[[1]]$operation$outflow,1,sum) observed<-observed+rnorm(length(observed),mean(observed)*0.2,sd(observed)*0.1) GOF(simulated,J1,observed) ``` ## See Also `sim`

GOF function