Questions tagged [forecasting]

Prediction of the future events. It is a special case of [prediction], in the context of [time-series].

Filter by
Sorted by
Tagged with
1
vote
1answer
18 views

Cyclicality in time series

The high amount of cyclicality in the lynx time series makes it very difficult to model with ets and ...
0
votes
0answers
14 views

Forecasting a binary time series [duplicate]

My (real) problem is as follows: I have a weekly time series about orders of a given product in a specific bar. Let's say that we have a 0 when the bar doesn't order in that week and 1 when it does. ...
0
votes
0answers
8 views

estimate “et” error terms / residuals of SARIMA from equation

I want to estimate manually (from equation/algorithm) the predicted values of the model "(2,1,0) (0,0,2) [7]". However, the equation estimates the fitted values. I want to know how estimate "et" to ...
0
votes
1answer
33 views

Incorporate additional information in Stock Forecasting

I am trying to forecast stock of health products. Other than historical stock quantity, I would have some other information, e.g.,: Certain stocks are in compete of each other; Certain stocks are ...
0
votes
0answers
11 views

Is applying an ARMA model to a stationary series the same as applying it to a trend and seasonally adjusted series?

Is it true that regular differencing and seasonal differencing of a time-series to achieve stationarity, is the same thing as adjusting a time-series for trend and seasonality? If the above statement ...
0
votes
0answers
18 views

KPSS test thinks that regression is spurious

It should be obvious that there is a relationship between the market price of black pepper and the market price of white pepper. ...
0
votes
0answers
13 views

Detecting spurious regression by testing the residuals

A linear regression between "Number of Australian Air Passengers" and "Rice Production in Guinea" reveals a "strong" but probably spurious relationship between the two time series. ...
0
votes
0answers
13 views

Is Box-Jenkins approach to time-series prediction and forecasting similar to Unobserved Components models approach?

How I understand the Box-Jenkins Method in a nut-shell is that a time-series model has signals that can be identified by weighting its own past lagged values, or weighting its owned past errors or ...
1
vote
0answers
71 views
+50

Estimate the time series like an event was never happened

I have data from a website where a specific advertising campaign happened a couple of years ago. What I want to do is to estimate how the signups on that website would have been without that big ...
0
votes
1answer
35 views

Is time series analysis suitable for long term predicting/forecasting?

Can I use time series analysis to predict/forecast long term ? Example using ARIMA, how can I explain the back of the theory its?
0
votes
0answers
19 views

ARIMA(0, 1, 0) or ARIMA(0, 0, 0) for Stock log-Returns Forecast

I'm trying to forecast the log-returns of Amazon's stocks using the ARIMA model, so I went through the traditional procedure of examining the autocorrelation plot and the partial autocorrelation plot ...
2
votes
2answers
2k views

Special method for forecasting on time-series clusters in R?

I'm doing a project related to identifying sales dynamics. My database contains 26 weeks after launching the product (so 26 time-series observations equally spaced in time). I used two methods of ...
1
vote
3answers
355 views

XGboost for Time series - using lag of target variables

I'm trying to make a time series forecast using XGBoost. I have already added many time related variables - day_of_week, month, week_of_month, holiday. I want to add lagged values of target variable ...
5
votes
1answer
683 views

How to specify when a level shift begins and ends or in the case of data series with multiple level shifts how to id when one level shift beings/ends?

I am working on forecasting airport delays the data looks like this It looks like there is a structural break around 2004 where theres a huge increase and then a huge decrease around 2009. I am ...
6
votes
3answers
9k views

R Time series forecasting: Having issues selecting fourier pairs for ARIMA with regressors

I've been working on some various time series forecasts and I've begun to notice a trend (pardon the pun) in my analyses. For about 5-7 datasets that I've worked with so far, it would be helpful to ...
1
vote
0answers
94 views

Neural Network regression on time series

I want to predict the trend values of a time serie [Y] based on the effect of other 10 input variables which can also have interaction. Since the combination of interaction between the inputs is ...
0
votes
1answer
698 views

Simulation and mathematical notation for ARIMA(0,1,1) with drift

I am attempting to write the mathematical model for and also simulate an MA(1) process that has drift (in R). I have referenced ARIMA (0,1,1) or (0,1,0) - or something else?, Simulation of forecasted ...
1
vote
2answers
31 views

How do I forecast quarterly public expenses based on annual budgets and potentially other variables?

I have some time series data from 2008 and forward (see below) on quarterly public expenses and annual public budgets. I would like to forecast the last two quarters of 2018 as precisely as possible, ...
0
votes
0answers
41 views

If prediction intervals become narrower when less historical data is provided, how do you justify using a full range of data?

In forecasting (ets) annual data, I notice that when I use the full data set of 10 years, the prediction intervals are much wider than when using an abridged version of the data set (5 years). I ...
4
votes
2answers
3k views

Why do the 95% confidence limits in ARIMA models widen at the forecasts?

Can someone please explain why when I do an ARIMA model the forecast's 95% confidence interval widen?
1
vote
1answer
624 views

Which model to use between VAR and VECM for the following problems (conditions)?

I have three variables (monthly for 25 years) including wages (e.g. skilled and unskilled) and food price (P). I am interested to see if there any relationship exist between them, either short or long ...
0
votes
0answers
8 views

How to find FFT for a window period of a given large time series data?

If i binned time series data for particular time interval 't' and choose a window period of lets say 5 bins and converted into n rows as train data(5 bins for each row) and a y_value(need to be ...
0
votes
0answers
20 views

Diebold Mariano test Nested Models

I have computed forecasts with 4 different methods, namely OLS, Elastic Net, Cubic splines in combination with Lasso, and Neural Network. All models use the same set of base variables, except cubic ...
0
votes
0answers
5 views

Significance of hyper parameters in the DHR model in R forecast package

The Dynamic Harmonic Regression model in R requires the input of parameters K, the length of which depends on the number of seasonality in the forecast data. According to https://otexts.com/fpp2/dhr....
0
votes
1answer
23 views

ARIMA Time Series Simulation - Media Mix Model

I have designed and tested a time series model where I am able to examine the impact of various marketing channels on dependent variables (Such as sales, revenue, website traffic, etc). The model has ...
0
votes
2answers
2k views

Time series analysis for predicting a binary outcome

I'm fairly new to time series analysis. I want to analyze two series of variables in a span of time to predict a binary outcome. For example i collect data over time at my home of two variables: ...
0
votes
0answers
15 views

How is the method of Eviews dynamic forecasting? [closed]

One [answer]1 says that dynamic forecast use forecasted value instead of actual value.Yes it is logical. But other answer says dynamic forecast use n step ahead.Example if you want to 10 days or 100 ...
1
vote
1answer
278 views

SAS: Holt Winters Forecasting

If I have an estimate for Holt Winters model as the attached image. How do I interpret the estimates i.e the level, trend and seasonal smoothing weight.
8
votes
1answer
1k views

How to compare forecasting methods?

I have several intermittent data. Based on those data, I would like to compare several forecasting methods (Exponential Smoothing, Moving Average, Croston, and Syntetos-Boylan), and decide whether ...
0
votes
0answers
20 views

Dont we accept the hypotheise of efficent market ıf we use ARIMA model to forecast or predict? [closed]

I estimate ARIMA models or another models that explain now price with past pirce. If I use this models , already ı reject efficient market hypothesis? I write master thesis and my teacher asked me ...
0
votes
0answers
6 views

R forecast script - how to ignore current month in the calculation? [migrated]

I am using the following R script (in Tableau) to do monthly forecast, using package "forecast". It works without errors but I would like to exclude current month from the calculations. ...
0
votes
0answers
10 views

Is it possible to to compare ARIMA and ARMA-GARCH model with different series?

I have some questions with model compares ion and forecasting. The row data (quarterly traffic accident numbers) is not stationary but it is stationary at first difference. we can model and forecast ...
2
votes
1answer
38 views

Can I give continuous rank probability score (CRPS) to Diebold-Mariano (DM) test?

I would like to use DM test for probabilistic forecasting case. My initial thinking was to give CRPS of two forecasting methods instead of raw forecast errors, where CRPS is calculated using ...
1
vote
0answers
12 views

HAR model estimation in R studio [closed]

After splitting my data as the "in and out-of-sample" for volatility forecasting purpose in R, I estimate HAR model, but my estimated HAR model is for the whole sample. It does not estimate for the in ...
0
votes
0answers
16 views

Why BSTS model gives very different forecasts depending on length of testing set?

When I run a BSTS model in R, I get a finished model from a data set, and when I use that model to predict, for example, like this: predict(model3,newdata=futuredata) -> pred_1 I get a set of ...
0
votes
1answer
37 views

Sarima : Fitting on train subset works but fitting on whole train does not [closed]

I use SARIMAX from statsmodels.tsa.statespace.sarimax in Python. I have a simple one column energy consumption dataset with 27679 rows. The frequency is Hour. I do hyperparameters optimization ...
3
votes
1answer
3k views

forecasting multivariate time series (with categorical variables) in R

I want to forecast future(next 20 days) sales with sample dataset. This is just a sample data and the actual data is from Jan 2014 to Dec 2016. As you can see, sales tend to increase as time goes by, ...
0
votes
1answer
30 views

Manually adjusting forecasting model bias

I am trying to build an efficient forecasting model to predict sales in the future. I managed to obtain a first pretty solid model using a LSTM network. However, it wasn't sensible enough to large ...
5
votes
1answer
53 views

Is ARIMAx a transfer function model?

I would like to know if the ARIMAx model is considered a transfer function model. If the answer is no, further explanation on what are differences would be appreciated.
1
vote
2answers
50 views

Forecasting daily data with zeros in Python

I'm currently testing some forecasts on daily sales quantities. However, out of ~2000 observations I have 16 zeros. How should I approach this? It's mainly Sundays and holidays that holds zero as ...
5
votes
1answer
245 views

Forecasting demographic census

What are some of the ways to forecast demographic census with some validation and calibration techniques? Some of the concerns: Census blocks vary in sizes as rural areas are a lot larger than ...
4
votes
2answers
83 views

Incorporating Prior Information Into Time Series Prediction

Suppose I have data on my child C's height measured every week. Presumably there is a positive trend, due to growth, and some noise due to measurement errors, and maybe even seasonality (winter boots ...
1
vote
0answers
15 views

Future event prediction methodology

I have a data set such that each data point is an "event" with features $x_1, x_2, \dots, x_n$ and the year of its occurence $y$. I want to train a forecasting model that predicts when an event of ...
-1
votes
0answers
13 views

How to plot the ARIMA fitted values of a time series in R?

I'm currently analyzing the stock market price indices for my undergrad research. Namely, ASPI: all share price index(abbrv:aspi) & SL S&P 20 (abbrv :std) auto.arima() gives me the following ...
1
vote
1answer
163 views

Predictions remain same for ARIMA model?

I have a table which has data CO2 emission of the world from 1960 to 2011. After going through some tutorial i performed ARIMA method on my dataset,but the prediction of CO2 emission for the next 10 ...
6
votes
1answer
663 views

forecast::auto.arima() is not returning a model with a differencing parameter when it should

I'm experiencing an issue in which it seems forecast::auto.arima() isn't returning a model with a differencing parameter when it should. Read through my reproducible example to arrive at the question. ...
3
votes
1answer
6k views

Why use differencing and Box-Cox in time series?

Why use Differencing and Box-Cox transformation in a time series? From what I read the usefulness of the procedures are Differencing: Making a time series stationary and stabilize the mean Box-Cox: ...
0
votes
1answer
21 views

Time series forecasting: How can I adjust my forecast to incorporate external predictions at a different time scale?

I have information about past and future values that I want to incorporate into my timeseries model (experimenting with ARIMA and other models) in order to predict the future at a more granular ...
0
votes
0answers
30 views

Forecasting time series for categorical variables

I have time-series data with daily sales for shops and sold items. I would like to predict the number of each product sold in each store. What is the best way to solve this problem? It is necessary to ...
0
votes
0answers
11 views

Treating seasonality in Partial Least Squares forecast

I've been looking for answers on this question but couldn't find concrete solutions so wanted to ask y'all. I have been playing around trying to forecast an economic/financial-related indicator with ...