plot.fitArCo {ArCo}

Plots realized values and the counterfactual estimated by the fitArCo function

Description

Plots realized values and the counterfactual estimated by the fitArCo function. The plotted variables will be on the same level as supplied to the fitArCo function.

Usage

## S3 method for class 'fitArCo'
plot(x, ylab = NULL, main = NULL, plot = NULL,
  ncol = 1, display.fitted = FALSE, y.min = NULL, y.max = NULL,
  confidence.bands = FALSE, alpha = 0.05, ...)

Arguments

x

An ArCo object estimated using the fitArCo function.

ylab

n dimensional character vector, where n is the length of the plot argument or n=q if plot=NULL.

main

n dimensional character vector, where n is the length of the plot argument or n=q if plot=NULL.

plot

n dimensional numeric vector where each element represents an ArCo unit. If NULL, all units will be plotted. If, for example, plot=c(1,2,5) only units 1 2 and 5 will be plotted according to the order specified by the user on the fitArCo.

ncol

Number of columns when multiple plots are displayed.

display.fitted

If TRUE the fitted values of the first step estimation are also plotted (default=FALSE).

y.min

n dimensional numeric vector defining the lower bound for the y axis. n is the length of the plot argument or n=q if plot=NULL

y.max

n dimensional numeric vector defining the upper bound for the y axis. n is the length of the plot argument or n=q if plot=NULL

confidence.bands

TRUE to plot the counterfactual confidence bands (default=FALSE). If the ArCo was estimated without bootstrap this argument will be forced to FALSE.

alpha

Significance level for the confidence bands.

...

Other graphical parameters to plot.

See Also

fitArCo

Examples

##############################################
## === Example based on the q=1 fitArCo === ##
##############################################
# = First unit was treated on t=51 by adding
# a constant equal to one standard deviation
data(data.q1)
data=list(data.q1) # = Even if q=1 the data must be in a list
## == Fitting the ArCo using linear regression == ##
# = creating fn and p.fn function = #
fn=function(X,y){
return(lm(y~X))
}
p.fn=function(model,newdata){
b=coef(model)
return(cbind(1,newdata) %*% b)}
ArCo=fitArCo(data = data,fn = fn, p.fn = p.fn, treated.unit = 1 , t0 = 51)
plot(ArCo)