I have a good understanding of ARIMA models but I've always found significant spikes in ACFs and PACFs that gave me the appropriate AR and MA parameters.

Now I'm dealing with a series that is more like an ARIMA(0,1,0) which I think is the same as a random walk? This random walk concept is a little new to me but I sort of understand it. My question now is how do I even create a model for this series?

I've seen some methods in the {forecast} package that might be the ones I'm looking for but I want to understand how they are different.

The functions that I am confused about are naive() and rwf(). It seems like both try to address the same random walk problem. But also, what happens if I just build an Arima() model with parameters 0,1,0? how is that different?

Lastly, once the model is built, how do I forecast for new data?

I have a good understanding of ARIMA models but I've always found significant spikes in ACFs and PACFs that gave me the appropriate AR and MA parameters.

Now I'm dealing with a series that is more like an ARIMA(0,1,0) which I think is the same as a random walk? This random walk concept is a little new to me but I sort of understand it. My question now is how do I even create a model for this series?

I've seen some methods in the {forecast} package that might be the ones I'm looking for but I want to understand how they are different.

The functions that I am confused about are naive() and rwf(). It seems like both try to address the same random walk problem. But also, what happens if I just build an Arima() model with parameters 0,1,0? how is that different?