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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75 views

Forecasting with after x lags values

I like to build a forecasting model where am allowed to use only l lagged values. That means the model should forecast only l lagged values like $y_{t}$ can be only predicted using values $y_{t-l}$, $...
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25 views

What are the one-step time series forecasting methods?

What are the time series forecasting models which purpose is to make just a one-step prediction? How do I statistically validate a time series forecasting model which purpose is to make just a one-...
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Machine learning models for time-series?

I am trying to make prediction of univariate time series with functions from forecast package like: ets,auto.arima and nnetar.During modeling I divide data in traning and test set.So first I traning ...
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41 views

Back-transforming forecast points and error bounds from a VAR model applied to alr-transformed compositional time series

The data I have a k=3 compositional time series from which I am trying to forecast future values. The series is compositional in that at each time ...
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12 views

Time series analysis video resources

I am kinda new in Data Science. My background is in Mathematics. I took some graduate-level statistics courses like the generalized linear model. I am interested to forecast future student enrollment ...
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18 views

Marketing with Statistics sources

Can you tell me about some books about Marketing topics, using R or Python? I'd like to cover: Cannibalization Models Marketing Mix Models Market Basket Analysis Share of Market Forecast Models
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1answer
67 views

Manually replicating an ARIMA forecast

I hate to ask this question but I am going insane and other links haven't solved this problem. I have a seasonal ARIMA with just over two years of weekly data ARIMA(0,1,1)(0,1,1)[52]. It's highly ...
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Time Series Forecasting: If my data is not autocorrelated, does this mean time series forecasting is not appropriate?

I'm new to time series forecasting and I'm finding some of the concepts a little counterintuitive compared to the usual statistical models I use (regression etc). I attempted to do an ARIMA on my ...
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Holt-Winters (or similar exponential smoothing methods) - equivalent to three-standard deviation for forecast variance?

I am trying to implement Heijunka - production levelling - for products at a manufacturer. My feeling is that one way to do this would be to use Holt-Winters estimates of volumes across time, and ...
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How to reproduce fitted ARIMA(0,1,1) values?

I am using R's forecast package's auto.arima function to forecast the following time series: ...
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25 views

Subscription Based Revenue Prediction

My dataset is on revenues from subscription-based (no commitment, can cancel any time). We have people signing up every year, continue paying for a few years and then gradually cancel the subscription....
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Do you clean the data before calculating MASE (Mean Absolute Scaled Error)

The denominator in the MASE calculation for seasonal data is the MAE of the seasonal naive forecast calculated in-sample. Is it common to do imputation before calculating the seasonal naive MAE or ...
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Forecasting with probabilities

I need help with how I should approach a forecasting problem. I have two tables like the ones below. ...
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49 views

Predictor for the sum of random variables

I have a random variable Y, which is a sum of N random variables $$Y=\sum_{i=1}^N Y_i$$ Some of the $Y_i$ may be positively or negatively correlated to each other and in fact many of them are. I ...
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26 views

multi-step forecast classification problem

There are multiple approaches for multi-step time series forecasting, mainly recursive strategy, independent and MIMO. If I want to predict whether an event is going to occur at some point in the ...
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1answer
75 views

Is average standard deviation a good way to measure forecasts accuracy?

I have a database of forecasts (ranging from 1 week to 4 weeks in advance) and one of experimentally recorded values for a specific index whose value ranges from 1 to 9 (most of the time it measures 2 ...
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What models or techniques should I use for forecasting sales by channels but also the total sum?

I need to build a model to forecast or predict monthly sales by channel, and at the same time predict the total global sales. A traditional regression model, training the model in monthly sales by ...
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19 views

Vector Regressions for Highly Correlated Variables

This is a theoretical question and no code is provided. I'm trying to forecast four, highly correlated variables; all are price series for regular gasoline in a very close region. When I've run a VAR ...
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59 views

Extract Method from tsCV when using auto.arima or stlf

I am using the forecast package in R --> https://cran.r-project.org/web/packages/forecast/forecast.pdf When I run the below code, does each rolling origin point use a different arima model to ...
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22 views

How is R producing these ARIMA forecasts?

I am trying to understand what R is doing to produce forecasts for a particular ARIMA model I fitted. I used R to fit an ARIMA (1,0,0)(1,0,0)[5] error model with the following data. ...
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58 views

Resources for learning the time series stuff they don’t (or didn’t) teach you

I at one point, a long time ago, had two years of graduate econometrics focusing on time series, plus more on micro cross-section techniques. I haven’t made much use of the time-series stuff for a ...
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24 views

I have I(1) dependent, two I(0) and one I(2) independent variables, which model I have to use?

I want inflation forecast. I have I(1) dependent, two I(0) and one I(2) independent variables, how can I check co-integration and which model I have to use? I was about to use ARDL or ECM model, but ...
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2answers
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Time series forecasting when historical data are provided in batches

I am working on a forecasting problem with hourly time-series data. Working on historical data I have deployed several models which take as input previous values e.g at time t-1,t-2,t-3... etc and ...
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1answer
86 views

Forecasting an index with google in R

I am trying to predict an index using Google Trend Data. I try to orientate myself by this paper. In this paper the authors use the three variables: Sales, Index and SearchFrequency to forecast the ...
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Customer next visit behavior forecast

I'm currently working with retail data about a store and the goal is to predict when each customer will visit the store again e.g customer id = 1 will probably visit again in 6 days(recency) My ...
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35 views

Defining bias in time series forecasts

What is the usual definition of bias in time series forecasts? I have seen in a few places that it is $E[y_t - \hat{y}_t|I_{t-1}]$. However, due to estimation $\hat{y}_t$ is a function of the past ...
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51 views

Forecasting with ARIMA models

I want to do a rolling window forecast on a time series but it seems the series is white noise ARIMA (0,0,0) with non-zero mean. But when I difference the dataset and model it with an ARIMA(0,1,1) I ...
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63 views

How to forecast low values in data more accurately than the higher values?

I have a scenario where I have to forecast small values in data more accurately than the higher values. I have data set as below ...
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1answer
39 views

Hourly forecast [closed]

I am trying to forecast hourly Oil prediction based on each product. The data is from 04-01-2018 to 14-01-2020. I used frequency 24.The problem is that data is irregular like some days are missing due ...
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66 views

Hierarchical Forecasting using exogenous variables at each sub level

I am newbie, exploring some concepts for Hierarchical Forecasting using exogenous variables. I am stuck at obtaining an efficient approach where I have to incorporate exogenous variables at each sub ...
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50 views

One year of daily data - Holt Winters

I am doing basically my first forecasting model in R and I have some questions. I used Airbnb data available from this Kaggle project: https://www.kaggle.com/airbnb/seattle I had to use statistic ...
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1answer
36 views

What kind of data suits ARIMA forecasting?

I understand that an ARMA series is of the form $y_t = \mu + \phi_{1} y_{t-1} +…+ \phi_{p} y_{t-p} - \theta_{1} e_{t-1} -…- \theta_{q} e_{t-q}$ Can any form of quantitative variable ( price, ...
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SARIMA Forecast Longterm Downsides [duplicate]

While doing several SARIMA Forecasts I do not understand why SARIMA Forecasting is only considered to be short term forecasts and other methods like regression are longterm? What are the downsides of ...
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107 views

How can i apply Random Forest regression in time series data [duplicate]

I have daily water level data of 1990 to 2010 with precipitation,solar,temperature humidity and wind data.I want to apply random forest method in this time series data for estimating water level.But ...
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Is there a name for forecasting present and past quantities based on present data?

I'm not talking about backtesting, where you simulate forecast results based on past data only. The situation I'm talking about is when a metric about the present or past hasn't been completely ...
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2answers
67 views

How to predict future of time series 1 with time series 2 with AR(I)MA?

Hey guys i am new in this forum. I am also new into programming with R or Stata(and programming in total, but i really would like to learn it). Currently I am writing a thesis about whether its ...
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0answers
36 views

How do i forecast a time series is about to cross a certain threshold

I have data coming in 10 seconds apart which is the temperature of a given room. It has a seasonality of 6 hours as it has 2 AC switching back and forth. Sometimes the AC in this room fails and thus ...
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125 views

Pmdarima Weekday only vs Weekend Only vs Whole Week Forecasting

I want to implement Pmdarima auto arima module in my daily forecasting process(I use Python and i don't use R). Regarding to different needs sometimes i need to forecast only weekdays or only weekends ...
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1answer
71 views

Seasonal difference in ARIMA

I have time series with frequency=7. ndiffsfunction (https://www.rdocumentation.org/packages/forecast/versions/8.10/topics/ndiffs) suggests first order difference ....
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1answer
56 views

Simulate multiple forecasts with fixed accuracy

I have a time series forecast along with actual historical data, and its accuracy (MAPE, probability coverage etc.) is calculated. Now I want to estimate how improving some or all of the accuracy ...
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14 views

Examine the below time-series plot of data. With reference to the graph, justify the chosen method for the analysis that has been started on the table

Please can I be provided with a good answer/justification for the question? I think there is one method and it is moving average? I am not sure though.
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How to interpret periodogram of py script results

I have 5 years weekly sales data,did primary detrending(using seasonal decomposition) on it and processed the dtrended data through periodogram script(Welch code) and got below results. However,am ...
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1answer
73 views

Dynamic Time Warping Univariate Time Series to aid in selecting Forecasting Model

I have approximately 174 univariate time series that I would like to forecast. These are all country observations that have been thoroughly cleaned with no outliers or missing values. I would like to ...
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1answer
60 views

Based on the graph & table, what method is used for the analysis that has been started on the table pictured?

Looking at the time-series plot of data (pictured), and looking at the table (pictured), what method and why has been chosen for the analysis that has been started on the table shown? I'm struggling ...
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54 views

Comparing two tests: Diebold-Mariano vs. Giacomini-White

What is (are) the main difference(s) between the Diebold-Mariano and the Giacomini-White tests of superior predictive ability? When does (do) the difference(s) matter?
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Does the steps outlined are the right way of finalizing and saving ETS models to perform forecasting using python?

I have 5 years of weekly sales data of different retail products and trying to implement ETS modeling.Data split has been done in a way that last one year data goes into test and remaining in train ...
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1answer
113 views

Should I use the Diebold-Mariano test year-by-year or on the overall forecast?

I have built two models, one ARIMAX and one VAR, to compare against a baseline ARIMA model to predict a weekly economic time series of interest. I am primarily comparing the accuracy of my models ...
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0answers
106 views

How to perform multi-step forecasting in holt-winter modeling in python

I am trying to implement demand forecast of a produt for a month ahead and then convert it to week wise. I have received 7 years of week wise sales data,did all necesary data preprocessing,train(up to ...
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1answer
157 views

Forecasting with mixed models

I need to forecast sales for a data set where I have the amount sold per item and week. There are also categorical variables that are supposed to be integrated into the model as random effects. What ...
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27 views

Fitting a Local Poisson model (Exponential Smoothing) [closed]

I am working through "Forecasting with Exponential Smoothing". I am stuck on exercise 16.4 on the part that states: The data set partx contains a history of ...

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