# Questions tagged [differencing]

Differencing is a time series transformation used for removing unit roots. It can be simple or seasonal (for seasonal unit roots), first-order or higher-order (for multiple unit roots), also fractional order.

10 questions
Filter by
Sorted by
Tagged with
24 views

### How to generate fitted values manually for a seasonal ARIMA model?

I am trying to get the fitted values for a SARIMA model, and I can only access the arima() or auto.arima() functions in 'forecast' package in R for benchmarking my results (which is probably not the ...
39 views

### Detrended data and ARIMA modeling

What data should I use in ARIMA modeling when I do detrending, is it the original data or the detrended one? Then, what is the d component of the ARIMA model, is it d=0 or d=1?
53 views

### Do differencing within ARIMA or do differencing first before fitting ARIMA

There is a similar question about differencing within ARIMA or before fitting ARIMA. It is stated from the answers that there are differences when differencing is done before fitting ARIMA from ...
11 views

### Differencing vs detrending and test candidates for Time Series

First time I write here but long since I first got into this interesting forum. Well, I'm getting involved with a Time Series forecasting project and I have a lots of questions in my head... but lets ...
34 views

### Math behind Differencing: Is White Noise Stationary?

I'm just starting to learn the math behind stationarity and differencing, so I apologize if this is a silly question. Lets say I have a non-stationary time series process (pure random walk) defined by:...
26 views

### ARIMA first order differencing shows strange pattern

I have came across with a strange issue when I employ a first order differencing to make the original time series stationary. The original ts is with 1-min recording interval and over 2months. Since ...
70 views

### How to work with multi-step forecasting on differenced time series

I have a financial time series that I wish to make 5 step ahead (t+5) forecasts on. As the series is non-stationary, I have differenced the series. For every time step t, the response variable is ...
39 views

### modelling on differenced data

I have a time-series data that I want to model using machine learning models like Lasso Regression, Ridge, elastic net, etc. However, in order to make it stationary, I difference the output variable, ...
I have two time series sequences. One is $y_t$, which is non-stationary, and the other is $x_t$, which is stationary. Suppose I would like to do a regression of $y_t$ on $x_t$ to forecast $y_t$. The ...
In the online forecasting book of Hyndman (https://otexts.com/fpp2/MA.html) firstly the use of differencing is explained. After that he shows the formula for a moving average model: y_t = c + \...