I would like to run a recursive regression using my variables residential_ddiff and interest_diff thus testing the stability of the coefficients of my variable interest_diff.
The issue occurs as I want the recursive regression to be run on the 1 lag in the window of [i:(i+10)] observations but keep getting the same error:
Error in merge.zoo(residential_ddiff[i], L(interest_diff, 1)[i:(i + 10)], :
all(sapply(args, function(x) is.zoo(x) || !is.plain(x) || (is.plain(x) && .... is not TRUE
Both time series are n=91 and stored as ts objects. I've tried using both ts and numerical objects in my loop.
I've attached a screenshot of my code. For loop in R
Gratefull for any help, thank you.
I've tried lots of different options. Both trying to coerce using the as.zoo() function as well as defining the current observation of residential_ddiff[i] both same error keep occuring.
Reproducable example:
library(dynlm)
# Creating two datasets
data_1 <- c(3.2705, -1.9710, 1.3821, 1.3194, -0.8008, 0.2832, 3.2705, -1.9710, 1.3821, 1.3194, -0.8008, 0.2832, 3.2705, -1.9710, 1.3821, 1.3194, -0.8008, 0.2832, 3.2705, -1.9710, 1.3821, 1.3194, -0.8008, 0.2832)
data_2 <- c(1.41, 0.33, 0.32, 1.53, -1.55, 0.73, 1.41, 0.33, 0.32, 1.53, -1.55, 0.73, 1.41, 0.33, 0.32, 1.53, -1.55, 0.73, 1.41, 0.33, 0.32, 1.53, -1.55, 0.73)
# Storing data in a dataframe
df <- data.frame(data_1, data_2)
# Making sure the dataframe are numeric
df1 <- mutate_all(df, function(x) as.numeric(as.character(x)))
# Creating variable to store coefficients
estimate.store <- matrix(ncol = 6, nrow = nrow(df1)-3)
# Loop begins
for (i in 1:(nrow(df1-3))) {
# Creating af dynamic linear regression with data 1 and the rekursive values of i:(i+3) for the first lag of data_2. Here the main issue arises, I think.
estimation.store <- dynlm(df1$data_1[i] ~ L(df1$data_2,1)[i:(i+3)], as.zoo(df1))
estimate.store[i,] <- c(estimation.store$coef[1], confint(estimation.store)[1,], estimation.store$coef[2], confint(estimation.store)[1,])
}
