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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1answer
641 views

Python ARIMA generates different predictions than SARIMAX for same orders

I was under the impression that Python Statsmodels SARIMAX with seasonal order parameters set to 0 will generate the same forecasts as ARIMA. But apparently the forecasts are wildly different. What ...
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346 views
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335 views

Residual autocorrelation and forecasting

My residuals are autocorrelated. Will this be a problem if I want to use the time series to do forecasting?
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2answers
26 views

Predictive Modelling to predict next period sales

I have a Customer data (20 periods) which contains Sales of each customer by Period P1,P2,P3 ... P20) (each period =14 days) Is there anyway to predict P21 period ? Can I used ARIMA or ETS keeping ...
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2answers
133 views

ARIMA (Statistical approach) Vs Regression approach to predict values

I have sales data of my organization for last 3 years and based on that I have to forecast Budget amount for next Fiscal Year. Sales data is available across different Geographies for various Product ...
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23 views

Short term(10 mins period) forecast using ARIMA [on hold]

I have 14 months(01/07/2018 to 30/08/2019) of one minute data, which I have aggregated to 10 mins block. So I have a data of dimension "61056 * 350". From this I am using 12 months of data to train ...
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51 views

Does smoothed data work better for time series forecasting with LSTMs?

I am training a 3-layer LSTM on time series data ($10^6$ training samples) to predict the next point in the time series, where there is no seasonality and the time series has been made stationary (...
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21 views

Is it possible to reconcile forecasts that are not only at different levels of an organizational hierarchy, but also measured in different units?

Consider the following scenario: I have a top line revenue forecasts in dollars for each of my corporate divisions or business units. I have capacity forecasts for each of my regional manufacturing ...
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17 views

Forecast from previous data for upcoming entry

I have data as given in Image I want to forecast for next Entries what will be their ATB - ATA (ATB-ATA column is the difference between ATA and ATB columns in days) I was trying this code but I don't ...
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1answer
17 views

tsCV auto.arima with xreg results in NAs

I'm using the tsCV function from the forecast package in R. I'm comparing arima with and without xreg. Without xreg I have no problems. But when I add xreg to the tsCV function I get a matrix of NAs. ...
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12 views

Sparse time series of non negative monthly defect percentage [on hold]

I want to forecast monthly defect percentages (multiple geography). Data is sparse and could be any percentage between 0-1. Please suggest a few transformations, modeling approaches and accuracy ...
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6 views

Uncertainty of additively combined models

I'm dealing with sales forecasts (time-series with few data points) for a company on a department level (one company consists out of multiple departments). My approach is it to build a time-series ...
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4answers
68 views

How to predict how the time series behaves in the future?

I was wondering how a statistician estimates how a time series continues. Namely, which is more accurate way to estimate the series? Draw a line between start and end points of the time series data ...
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21 views

Forecasting for Regression with sARIMA errors only needing new xreg's

I would like to get a better sense of why we only need new exogenous regressor data for forecasting Regression with sARIMA errors to new time periods, and not new time series data. Specifically what ...
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1answer
137 views

K in Fourier series - How to find value of K to use it in ARIMA?

I am using the forecast library for doing some time series forecasting. I need to forecast number of sold items. I am planning to add holidays as xreg in auto.arima. The holiday will be a 0/1 list, ...
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1answer
1k views

Usage of tsclean() in time series data

Consider the scenario, where I have many time series data. I have to make predictions for all.I made a ts object out the data. The data may contain outliers. I am not sure of it. But I always pass ...
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17 views

Narrowing down model for 2-independent variable time series forecasting

I've got a project I'd like to start working on and it roughly goes like this: I have past time series data for thousands of products that a company produces. There is a high weekly and yearly ...
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19 views

How to fit a regression model with ARIMA errors on the seasonally adjusted component of a time series (in R)?

I want to do these two things (combined) with a time series T: forecast the seasonally adjusted component of T (STL used for the decomposition) and "add back" the seasonality (I assume that the ...
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1answer
130 views

Flat forecast of trended time series data in r

I have a monthly time series of online visits for last 3 years starting from Jan 2016 to Dec 2018 and need to forecast for 2019. The data clearly has an upward trend although no seasonal lags ...
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1answer
1k views

how to help the tree-based model extrapolate?

The following example borrow from forecastxgb author's blog, the tree-based model can't extrapolate in it's nature, but there are definitely some method to combine the benefit of tree model (...
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17 views

Summation tricks [closed]

How can simplify this expression $$\frac{2|k|}{n}{\sum_{k=1}^{n-1}(\phi^k})$$ given that $|\phi^k|<1$
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2answers
2k views

Determine best ARIMA model with AICc and RMSE

I have done a training set to fit different ARIMA models and then a test set to assess their performance (with R). From what I understood, I can use the AICc to determine the best model by choosing ...
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19 views

ML preprocess to achieve stationarity

I would like to use Machine learning models on top of multivariate time series data to forecast long horizons (for example 400 items and their historical sales in the last year & content features)...
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1answer
245 views

Suggestions for Neural Network Structure for Time-Series prediction with constant covariates

I've been working on a time series prediction problem and wondered if someone has run across a similar problem structure & can make a suggestion on how to structure the training data, network, or ...
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1answer
41 views

Is it possible to forecast multivariate time series using exponential smoothing equations? If yes what are those equations?

I know we can forecast univariate time series using different models of exponential smoothing , but am searching for whether same can be extended to multivariate time series and if yes what are those ...
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1answer
73 views

book recommendation: statistics (time-series) for small samples [closed]

I was hoping someone could recommend a good book on statistical methods for time-series on small data samples. We are really looking to do some forecasting/extrapolation given 13 years of previous ...
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1answer
209 views

Adding noise to time series data to increase training data

I am dealing with a weekly time series forecasting problem and I am currently investigating the use of an LSTM to make a multi-step forecast for a univariate time series. I actually have a ...
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20 views

weekly forecasting

I am building a weekly forecasting model using dynamic harmonic regression model with Arima errors and Fourier terms. My understanding is that Fourier terms take care of seasonality of any length ...
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25 views

Capturing cycles in time series with Fourier

In time series regression with Fourier, Fourier terms are limited to maximum half of the frequency of time series to capture seasonality. my question is: Can we extend Fourier terms beyond half of ...
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1answer
444 views

What is the difference between ARMA+Fourier and TBATS model?

I am just wondering that, in terms of the multi-seasonal time series forecast, what is the difference between using auto.arima find the ARMA order, then fit ...
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1answer
27 views

time series forecasting - predicting the next 24 hours

I have much the same problem as predict-the-next-24-hours, I have several years of hourly data of demand, and I would like to predict the next 24 hours. Ignoring the multi-seasonality issues - is it ...
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1answer
15 views

WMAPE / WAPE for the evaluation of time series with positive and negative values

I have a time series y that has both positive and negative that I want to predict. For the prediction I normalize the values to a range between 0 and 1. If I give ...
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0answers
23 views

Prediction interval for multi step forecast

If I have a multi-step forecast of some timeseries, where the model is some auto-regressive function y[t] = f(y[t-1],x1[t],x2[t]) is it a valide approach to use sections of historical data to train ...
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0answers
33 views

Adjustment of the forecast of a time series for the analysis of a system

I have a simulation model of a system which receives a forecast of a time series as input. In my scientific work I would like to examine how the performance of the simulation model behaves in relation ...
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1answer
320 views

Forecasting energy consumption with ARIMA and regressors

Known data, 4 years of daily energy consumption correlated with temperature, seasonal calendar and holidays. Required forecasting for next days depending on known variables like temperature and ...
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0answers
38 views

Demand forecasting

I am forecasting number of phone calls (y) i ll be getting based on the products sold(x) and I am doing the following: (forecasted y) = (y/x averaged for past three weeks) * (forecasted x). 1. Please ...
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23 views

Improving accuracy in time series forecasting [duplicate]

I am trying to forecast a very typical sales data. I have tried Arima, ETS, Holtwinters and even neural networks but I can't get a model with more than 40% accuracy [Absolute sum of(forecast-Actual)/...
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31 views

What is a Good Error Target

I am modeling a forecast for product categories using auto Arima in R. I'm getting MAPE of between 9-15% on average. We don't have any historical records of forecasts vs actual so I don't know how ...
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1answer
70 views

Should I avoid mixed ARMA models?

I have hourly demand data for taxi rides that spans several years into the past. I want to use it in order to forecast future demand (for the next day). Robert Nau warns against the usage of a mixed ...
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0answers
85 views

Forecasting many stores sales with optimal reconciliation and regression

I am forecasting many stores sales via the optimal reconciliation approach. The problem is that forecasts are not as accurate as I would like. Edit: Part of the problem is that a small subset of ...
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3answers
452 views

Can simple exponential forecasting be used for a non stationary series?

I have a non stationary series with trend and seasonal components. I want to use simple exponential smoothing ONLY for forecasting. Does the series need to converted to stationary before using SES? If ...
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0answers
19 views

What forecast method is correct to apply to data in range -1 to 1

I have metrological data they strictly have range -1 to 1. For example -0,97654 0,0376544 0,049765976 -0,578 measurement values are tied to a point in time ....
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38 views

Any ideas on how to forecast this timeseries?

I have the following timeseries and unfortunately no other information except time and holidays. What methods could work for a probabilistic forecast of this? I thought about some regime changing ...
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2answers
481 views

Capture seasonality - ARIMA in R

I have a time series Y, for one year and measures taken every 15 minutes. The data show clear seasonality, both daily and weekly. I would like to see the seasonality in the models. I tried various ...
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2answers
3k views

Difference between forecasting accuracy and forecasting error?

I am working on a demand forecasting project and I am puzzled by the client's standards of forecast evaluation. The MAPE (Mean Absolute Percentage Error) with the sample data Forecast = 300 and Demand ...
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1answer
24 views

auto.arima with an input of another series

Two time series, which are related to each other. I want to see if "order" helps in predicting sales, by running auto.arima ...
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1answer
21 views

Why forecast::accuracy() mape is working with 0/0?

I'm learning now some metrics of goodness about time series forecasting, using the forecast package, but I'm stuck in something that surely I've not understood well....
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1answer
471 views

Forecasting with mixed frequency data

Just a general question that I couldn't find too much on. What would be some good approaches to one step ahead forecasting of financial time series with mixed frequencies? Often a lot of the ...
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2answers
2k views

What's a time series model for forecasting a percentage bound by (0,1)?

This must come up---the forecasting of things that are stuck between 0 and 1. In my series, I suspect an auto-regression component, and also a mean-reverting component, so I want something that I can ...
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0answers
16 views

What are good public datasets for time series analysis with “certified” (by papers in the literature) good predictors of the target variable? [closed]

I have to test different models for time series forecasting and predictors (exogenous covariates) goodness evaluation and I would like to use datasets used in relevant scientific publications that ...