summary.CausalMBSTS {CausalMBSTS} R Documentation

## Summary of causal effect estimation results obtained with CausalMBSTS

### Description

The method extracts and computes various summaries of the causal analysis with CausalMBSTS.

### Usage

## S3 method for class 'CausalMBSTS'
summary(object, ...)


### Arguments

 object An object of class 'CausalMBSTS', a result of a call to CausalMBSTS. ... further arguments passed to or from other methods (currently not used).

### Value

Returns an object of class summary.CausalMBSTS, which is a list of data frames corresponding to each date provided in horizon (or its default value) with the following columns:

 mean Estimated average causal effect lower Lower bound of the two-sided (1-alpha)% credible interval. Note that alpha parameter is inherited from the object object. upper Upper bound of the two-sided (1-alpha)% credible interval cum.sum Pointwise effect cum.lower Lower bound of a (1-alpha)% credible interval of the pointwise effect cum.upper Upper bound of a (1-alpha)% credible interval of the pointwise effect bayes.pval Bayesian p-value for the average causal effect pct.causal.eff Probability of a causal effect (%)

### Examples

set.seed(1)
t <- seq(from = 0,to = 4*pi, length.out=300)
y <- cbind(3*sin(2*t)+rnorm(300), 2*cos(2*t) + rnorm(300))
dates <- seq.Date(from = as.Date("2015-01-01"), by = "week", length.out=300)
int.date <- as.Date("2020-02-27")
y[dates >= int.date,] <- y[dates >= int.date,]+2

# Causal effect estimation
causal.2 <- CausalMBSTS(y, components = c("trend", "cycle"), cycle.period = 75,
dates = dates, int.date = int.date, s0.r = 0.01*diag(2),
s0.eps = 0.1*diag(2), niter = 100, burn = 10)

sum.causal.2 <- summary(causal.2)
print(sum.causal.2, digits = 2)
sum.causal.2\$horizon_default



[Package CausalMBSTS version 0.1.1 Index]