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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6
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2answers
415 views

Looking for advice regarding model selection for forecasting (dynamic?) panel data

I'm looking for some advice on selecting an appropriate forecasting model for panel data. I'm just starting out in the field and would appreciate any hints or rules of thumb to help make such ...
6
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1answer
901 views

How to make a combination (aggregation) of quantile forecast?

Framework. Fix $\alpha\in ]0,1[$. Imagine you have $n$ $\alpha$-quantile forecast methodologies that give you, at time $t$ for look ahead time $t+h$, an estimation of the quantile of wind power. ...
6
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1answer
5k views

ARIMA and external regressors in SAS and R

So I remember reading somewhere that when we have external regressors, auto.arima cannot make correct predictions for the order of difference for either ...
5
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1answer
8k views

Regression with ARIMA(0,0,0) errors different from linear regression

A Regression with ARIMA errors is given by the following formula (saw on Hyndman et al, 1998): $Y_t = b_0 + b_1 X_{1,t} + \dots + b_k X_{k,t} + N_t$ where $N_t$ is modeled as an ARIMA process. If ...
5
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1answer
2k views

how to help the tree-based model extrapolate? [duplicate]

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 (...
4
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2answers
9k views

Forecasting Time Series: Stationary vs Non-Stationary

Let's say that I have a non-stationary time series and that the series can be transformed to a stationary series using a first difference. If I want to forecast this series using ARIMA then what is ...
3
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1answer
908 views

How can I be confident about my forecasts and improve my methodologies?

Background I usually do a fair amount of forecasting using ARIMA, linear or multivariate regressions, polynomial trends, etc. A lot of this forecasting is for simplistic use and not really basis for ...
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2answers
10k views

Shall I use weekly or monthly data for forecast?

I seem not to find this in any textbooks. So I post these questions. Is monthly data better than weekly data for forecasting? Can there be seasonality in weekly data? Most software/methods don't ...
2
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2answers
26k views

What's the minimum sample size required to do a time series analysis?

I'd like to know the minimum number of monthly data points required to do time series analysis with the seasonality effect in forecasting. I read some articles & they were saying that 50 or 60 ...
11
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1answer
933 views

What do I do when values of AIC are low and approximately equal?

Chris Chatfield, whose many quality books and papers I enjoyed reading, in (1) gives the following advice: For example, the choice between ARIMA time-series models with low and approximately ...
9
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4answers
419 views

How should I approach this binary prediction problem?

I've got a dataset with the following format. There's a binary outcome cancer/no cancer. Every doctor in the dataset has seen every patient and given an independent judgment on whether the patient ...
8
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2answers
9k views

auto.arima does not recognize seasonal pattern

I have a daily weather data set, which has, unsurprisingly, very strong seasonal effect. I adapted an ARIMA model to this data set using the function auto.arima from forecast package. To my surprise ...
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2answers
2k views

Multilinear regression vs. Time Series

I have sale data for 3 years by week.I need to predict sales for the next year by week. The business requested that some categorical values and numeric values (so for example category, product ...
7
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2answers
7k views

Avoid negative results in Holt Winters forecasting

I understood that Holt Winters forecasting may results in negative values due to trending. I did reduce trending component value, but still forecast values are negative territory. Our data set will ...
7
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2answers
448 views

Does a density forecast add value beyond a point forecast when the loss function is given?

Density forecasts are more universal than point forecasts; they provide information on the whole predicted distribution of a random variable rather than on a concrete function thereof (such as ...
6
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3answers
2k views

Forecast accuracy metric that involves prediction intervals

I'm in the process of generating a time series forecast for a company's product revenue and am looking for some way to show accuracy over time - e.g. after say 6 months they want to see how the actual ...
6
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2answers
3k views

Length of Time-Series for Forecasting Modeling

I'm working with mixed model for forecasting analysis. One of the decision that we want to take for the modeling is length of time-series, whether it should be 2 years or three years. So my question ...
5
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1answer
2k views

Forecasting daily time series sales revenue with many zero entries

I have been trying to forecast the sales revenue of different product groups (the displayed sales revenue is aggregated over all products for each day e.g. smartphones with different prices as one ...
5
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2answers
6k views

Arima Model with weekday dummy variables Forecast

I'm trying to create an Arima model and forecast it ahead the next 20 hours using the code and data below. When I look at the median of df$tri for each hour and broken down by day of the week, each ...
5
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1answer
766 views

Are both ARIMA and Exponential Smoothing special cases of State Space models?

From the literature I gather that exponential smoothing models can be recast as special cases of state space models. I haven't seen similar references w/r to ARIMA being considered state space models,...
5
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1answer
1k views

How do you create variables reflecting the lead and lag impact of holidays / calendar effects in a time-series analysis?

I am working on a time-series project in which I am forecasting the daily activity of something (let's call it 'Y') based on three years of historical data. I know that Y is affected by calendar ...
4
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1answer
12k views

Which is the best accuracy measuring criteria among rmse, mae & mape?

I have created training set and test set from my data. Then I performed auto.arima() and ets() in R on the training set to predict one-step ahead forecasts. These were then compared with the test set ...
4
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0answers
3k views

Hold out sample vs. cross validation for time series, and how to perform in R

I think out-of-sample validation testing for accuracy is essential in initially judging what time-series forecasts to use. In any case, I've been doing some reading on the two most common methods, ...
4
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2answers
6k views

How to obtain confidence limits of predicted values in ARIMA?

How can one obtain confidence limits of predicted values in ARIMA?
4
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1answer
7k views

One step ahead forecast with new data collected sequentially

Hi all I'm trying to do one step ahead forecast. Lets say I have 1000 data and fit an ARIMA model with it and then I do a forecast for one period ahead. When I get more data I would like to forecast ...
3
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1answer
2k views

Time series: probability to exceed a certain threshold

I'm a beginner and I have a generic time series and I want to know the probability that it reach a certain threshold in the future. For example, the time series is day average temperature and I want ...
3
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3answers
22k views

What is one-step ahead static forecast?

I was using Eviews, and I noticed that there is 'dynamic forecast' and 'static forecast' in the option. But I don't know what is the difference, would any one tell what are they? But I know that both ...
3
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2answers
2k views

Proper ways to perform time series and ARIMA

Note that I do most of my analysis using R and Excel. Let's take this data set for example. I modified it as the data itself is proprietary: the years are also different: ...
3
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1answer
432 views

Forecasting handbooks

In engineering, we usually have Handbooks that pretty much dictate the state of the practice. These books are usually devoid of theory and focus on the applied methodology. Is there a forecasting ...
3
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2answers
2k views

ARIMA Model configuration for hourly forecasting problem

I have a database based on hourly data and I need to forecast next 24h of a single variable. I was thinking about applying an ARIMA model with some exogenous variables but I don't succeed to configure ...
3
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2answers
653 views

Puzzled by derivation of time series prediction based on its log

From Introductory Time Series with R: If the random variation is modelled by a multiplicative factor and the variable is positive, an additive decomposition model for $\log(x_t)$ [where $x_t$ is ...
3
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3answers
21k views

What is the distinction between short term and long term forecasting?

I often see forecasting methods described as long term or short term methods. I assume the difference between short term and long term forecasting cannot just be the amount of time. I assume this ...
3
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2answers
2k views

Time Series Forecast / Transfer Function

I'm trying to interpret the forecast values from an ARIMAX function, and I'm confused about what's happening in the actual forecasted values as I change the values for the predictor during the ...
3
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2answers
3k views

Using exponential smoothing to forecast irregularly spaced data in R

I'd like to use exponential smoothing to forecast the following data. The data is daily based. Because of some policy reasons, every $29^\text{th}$, $30^\text{th}$ and $31^\text{th}$ of each month, ...
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1answer
1k views

Measuring forecast accuracy

We're forecasting sales data for one of our clients on a weekly basis. Sales is forecasted for each organizational unit. The sales data is forecasted via different algorithms and/or algorithm ...
2
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0answers
91 views

Regression: Causation vs Prediction vs Description

In my experience it seems me that the interpretation about regression, its meaning and its scope, are debatable and great confusion exist about those things. It seems me that confusions are not go ...
2
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1answer
179 views

Single prediction vs. summing more granular n-step ahead predictions

Say I want to predict the total rainfall for the next 365 days based on a set of predictors and daily historical observations. I could build a model that predicts annual rainfall and make a single ...
2
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1answer
6k views

How to forecast from VECM (in R)?

I am interested in forecasting with a vector error correction model (VECM). I am facing a problem of not being able to transform a cointegrated series into a VECM model using the stationary series. ...
2
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0answers
4k views

auto.arima and Arima (forecast package)

I am facing a strange issue with the auto.arima() function. On a dataset named data, I run the following code ...
2
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2answers
2k views

Obtaining the SarimaX equation from the arima coefficients

I have a SarimaX model with three regressor variables: ...
1
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1answer
79 views

Make daily business data stationary for ARIMA

For my master thesis I have a dataset with the daily count of orders from a company over ten years. Naturally this data follows strong seasonality with almost no orders on the weekend. To fit an ARIMA ...
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2answers
261 views

Is my Data stationary? KPSS, ADF Tests and ACF

I already differenced my Data by 1 and i am not sure whether my Data is now stationary or not. I perfomed an KPSS and ADF test in order to help me decide if it is. I think it is stationary but im not ...
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2answers
1k views

Coefficient Significance in Regression with Arima Errors

In the R package forecast, when you run dynamic regression (regression with arima errors), the coefficients and their standard error are output, but there is no significance test available for the ...
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0answers
3k views

Forecasting Hourly Time Series based on previous weeks and same period in previous year/s

The Problem I have been tasked with a similar problem to that described in Forecasting hourly time series with daily, weekly & annual periodicity. My data shows the number of times that one of ...
1
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1answer
2k views

How to regress a time series of proportions?

Every month, an organization surveys some of its customers (the total number of customers is also known). The sampled customers answer a survey with a dozen or so questions; sometimes, customers don'...
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3answers
2k views

Daily forecasting

We have three years of data for online visits at a daily level. We want to forecast the daily visits for the next 90 days. What would be the best method to capture weekday seasonality , holiday ...
0
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0answers
508 views

Forecasting time series with missing data and irregular intervals

I have a data set of medical drug stock levels at health centres and I want to forecast monthly consumption over the following 3-6 months. However about 30%-40% of the data is missing and some of the ...
0
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1answer
800 views

Forecast evaluation for rolling forecast [closed]

I have rolling forecast for each month. I would like to do some forecast evaluation. How do I do this?
9
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1answer
739 views

Conditions for cyclic behaviour of ARIMA model

I'm trying to model and forecast a time series that is cyclic rather than seasonal (i.e. there are seasonal-like patterns, but not with a fixed period). This should be possible to do using an ARIMA ...
9
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2answers
471 views

Bias-variance decomposition: term for expected squared forecast error less irreducible error

Hastie et al. "The Elements of Statistical Learning" (2009) consider a data generating process $$ Y = f(X) + \varepsilon $$ with $\mathbb{E}(\varepsilon)=0$ and $\text{Var}(\varepsilon)=\sigma^2_{\...

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