Questions tagged [forecasting]

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

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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 ...
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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 ...
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584 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 ...
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736 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 ...
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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 ...
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137 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 ...
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1answer
765 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 ...
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41 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, ...
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48 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 ...
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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?
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714 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 ...
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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 ...
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38 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 ...
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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....
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31 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 ...
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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: ...
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300 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.
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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 ...
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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 ...
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88 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 ...
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27 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 ...
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22 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 ...
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1answer
68 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 ...
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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, ...
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31 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 ...
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72 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.
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89 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 ...
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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 ...
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121 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 ...
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18 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 ...
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1answer
182 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 ...
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1answer
815 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. ...
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7k 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: ...
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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 ...
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39 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 ...
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15 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 ...
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33 views

How to Recursively Predict a Time Series Using Neural Networks

I am currently using neural networks to forecast an electrical demand time series. I am trying to create a forecast for the following day given previous observations at half hourly intervals. My ...
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242 views

Meta-Analysis on Effect Sizes with 95% Bayesian CI from CausalImpact R package

I am using the CausalImpact package in R to calculate the impact of a marketing intervention using Bayesian Structural Time Series. This methodology and package is explained in Broderson et al. 2015 ...
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1answer
43 views

Time series Data : Regress absolute values or regress the %growth of the values?

I am doing a time-series data analysis. The idea is to produce a forecast from the regression output. I am regressing Air traffic passengers of country A with GDP/capita of country A. I am getting ...
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15 views

time series forecasting - ljung-box test - degrees of freedom to subtract when working with breaks

I'm working on a differentiated seasonal time series with 2 breaks and non-zero mean. So, besides the constant i've got 2 dummies for breaks correction. Question: when performing LB test, if my model ...
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131 views

Big Mart Sales Prediction Problem

I hope that some of you are familiar with Big Mart sales prediction data that was provided by Analytics Vidhya as a contest. The problem statement of on the website is as follows: The data ...
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160 views

Estimating prediction interval of ARMA process using R forecast function

the theme is forecasting with ARMA models. I'm trying to understand how the R forecast function works if applied to an ...
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2answers
180 views

Will ARIMAX or exponential smoothing forecast a short time series better?

The objective requires to predict GROSS NPA for 6 months and provided with 2 years of data i.e., around 24 observations. So, which of the method will provide better forecast?
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Vector Time Series: Capturing Systematic and Nonsystematic Patterns in Multiple Datasets | Financial Option Data

How does time series work with multiple time series data sets on the same index? For example, suppose I were a utilities company. Suppose I have the electricity usage of two homes, each indexed for ...
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953 views

Forecasting a ARIMA(1,1,1) model

ARIMA(1,1,1) process with constant term $\mu$ is $X_t=\alpha X_{t-1}+\mu+Z_t+\beta Z_{t-1}$ where $Z_t$ is white noise with mean zero variance $\sigma ^2$. Find one step and two step ahead forecast ...
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162 views

How to do regression on a time series by learning from historical time series?

I have a data set of customer purchases from the day of their registration to 120 days. There is a time series for each customer. However, some new customers do not have a history of 120 days yet. I ...
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Group time series examples

I am looking for group time series examples. I am working on two hierarchies and interested in interactions also. Couple of challenges I am facing I have 36 months data and many of the series has ...
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2k views

AIC versus cross validation in time series: the small sample case

I am interested in model selection in a time series setting. For concreteness, suppose I want to select an ARMA model from a pool of ARMA models with different lag orders. The ultimate intent is ...
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93 views

Forecasting in a state-space model from a Bayesian perspective

We have the following state-space model(or linear dynamical model): \begin{align} x_t&\sim N(Ax_{t-1},Q)\\ y_t&\sim N(Bx_{t},\Sigma) \end{align} I want to obtain a sample from $p(y_{T+1}\mid ...
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53 views

Big categorical data

I am trying to predict the price of used vehicles using three different models: Regression, ANN, and random forest. I am having 6 variables as an input for my model. One of my variables is the ...