code of zero-state Markov switching model

Here is an example code for a zero-state Markov switching model in R using the "MSwM" package:

library(MSwM)

#ulate data
set.seed(123)
x <- r(100)
z <- rbinom(100,1, 0.5)
y <- numeric()
y[z == 0] <- x[z ==0] + rnorm(sum(z == 0), = 0.1)
y[z == 1 <- x[z == 1] + rnorm(sum(z == 1), sd = 1)

# Fit the model
model <- msmFit(y ~ 1, k = 2, p = 0, sw = ~1, data = data.frame(y, z))

# Print the estimated parameters
summary(model)

# Make predictions
new_data <- data.frame(y = rnorm(10))
predict(model, newdata = new_data)

In this example, we first simulate some data where `y` is the response variable and `z` is the zero-state Markov switching variable. We then fit a zero-state Markov switching model using `msmFit()` function with `k = 2` indicating that there are two states, `p = 0` indicating that there is no autoregressive component, and `sw = ~1` indicating that we are modeling the switching variable as a constant. Finally, we make predictions using the `predict()` function.