I am working with the R programming language. In particular, I am using "Markov Switching Models" for the purpose modelling more complicated dataset with varying degrees of volatility. For this problem, I am using the "MSwM" package in R:
https://cran.r-project.org/web/packages/MSwM/MSwM.pdf
https://cran.r-project.org/web/packages/MSwM/vignettes/examples.pdf
I am following the first example from the "vignettes":
#load library
library(MSwM)
#load data
data(example)
#plot data
plot(ts(example))
#fit basic model
mod=lm(y~x,example)
#fit markov switching model:
mod.mswm=msmFit(mod,k=2,p=1,sw=c(TRUE,TRUE,TRUE,TRUE),control=list(parallel=FALSE))
The above code successfully creates the model - 2 "Regimes" have been identified:
Question: I checked the documentation of this package, and there does not seem to be any functions that allow you to predict future values of this time series. I did some research and it seems like the "Markov Switching Model" should allow you to predict future values of a time series, e.g. : https://stats.stackexchange.com/questions/90448/how-to-forecast-a-markov-switching-model
OR:
However, there does not seem to be a straightforward way to do this in R. Can someone please suggest how to resolve this problem?
Thanks
Related
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If my questions imply that I think about forecasting in a wrong way, please kindly correct my understanding of the subject.
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First, I train a model according to a given time series using the forecast package:
train <- forecast(ts(sin((2*pi)*seq(from=0,to=10,by=0.01)),frequency=100))
Then, once I get new time series i try seeing how well they fit the trained data, and by that finding anomalies.
Currently I'm using the accuracy function which doesn't seem to be the right tool for the job:
test <- ts(sin((2*pi)*seq(from=0,to=20,by=0.01))+sin((3*pi)*seq(from=0,to=20,by=0.01)),frequency=100)accuracy(train,test)
accuracy(train,test)
I also thought of somehow analyzing the residuals of the new dataset according to the trained model.
Does anyone have any good ideas as to how to optimize this task?