distreg_cfa {bayesdistreg} | R Documentation |
distreg
draws randomly from the density of counterfactual of F(yo) at a threshold
value yo
distreg_cfa(thresh, data0, MH = "IndepMH", cft, cfIND, ...)
thresh |
threshold value that is used to binarise the continuous outcome variable |
data0 |
original data set with the first column being the continuous outcome variable |
MH |
metropolis-hastings algorithm to use; default:"IndepMH", alternative "RWMH" |
cft |
column vector of counterfactual treatment |
cfIND |
the column index(indices) of treatment variable(s) to replace with |
... |
any additional inputs to pass to the MH algorithm |
robj a list of a vector of fitted values corresponding to random draws from F(yo), counterfactual F(yo), and the parameters
data0=faithful[,c(2,1)]; qnt<-quantile(data0[,1],0.25) cfIND=2 #Note: the first column is the outcome variable. cft=0.95*data0[,cfIND] # a decrease by 5% dist_cfa<- distreg_cfa(qnt,data0,cft,cfIND,MH="IndepMH",iter = 102, burn = 2) par(mfrow=c(1,2)); plot(density(dist_cfa$counterfactual,.1),main="Original") plot(density(dist_cfa$counterfactual,.1),main="Counterfactual"); par(mfrow=c(1,1))