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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4
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1answer
11k 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 ...
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4answers
904 views

How to forecast daily time series with weekends and holidays?

I'm having troubles choosing which approach to adopt when trying to forecast daily time series while taking into consideration special days like weekends and national holidays. The two methods I'm ...
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 ...
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2answers
5k views

How to obtain confidence limits of predicted values in ARIMA?

How can one obtain confidence limits of predicted values in ARIMA?
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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, ...
3
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2answers
691 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
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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2answers
578 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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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
18k 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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1answer
415 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
807 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 ...
2
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1answer
896 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 ...
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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
7k 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 ...
2
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1answer
5k 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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2answers
8k 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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1answer
118 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 ...
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2answers
1k views

Number of Days in a Monthly Forecast

So for the last few months I've been doing a lot of forecasting for my company and specifically I've been looking at monthly forecasts of total weight of different categories of products output's each ...
2
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1answer
7k views

Difference between first one-step ahead forecast and first forecast from fitted model

I'm doing some time series modeling using R and the forecast package, and found a minor difference I couldn't figure out. I'll reproduce my steps below. First, I ...
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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
1k 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 ...
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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 ...
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3answers
4k views

Seasonal ARIMA Modelling in R

I have monthly price data for a commodity from 2007 to 2017. You can find it in the following link: https://drive.google.com/open?id=0BxRCOgKAL4itcUZlOExrUmVOanc I need to forecast it using Seasonal ...
5
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1answer
6k views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
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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 ...
4
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1answer
184 views

Is modelling a structural change in a time series useful for statistical forecasting?

A colleague of mine is arguing that we should look into using some structural time series tools for improving our demand forecasting (I work in retail). I am a little bit skeptical. I don't see any ...
4
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2answers
364 views

Which method to use for load forecasting

I have smart meter data set that has consumption readings collected over a year and a half for every 30 mins. What I am trying to do is short term load forecasting. The data set has just three columns ...
4
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2answers
2k views

What is the proper name for a backward forecast?

Suppose in time series you have the data in a recent period and you would like to use that data to extrapolate backward to get estimates of the time series back in time. What do you call that? ? ...
4
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1answer
639 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,...
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4answers
3k views

Using information on both sides of a 'gap' in time series data for imputation

As with my previous question, I'm looking at ways to impute missing data in a hierarchical time series data. With al my other procedures, including the experimentation of imputation packages (...
4
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1answer
166 views

Accuracy of point forecasts vs. average accuracy of multistep forecasts?

It seems to me that it is possible that a forecasting model does very well on one step ahead forecasts (or on any other point forecast) but performs poorly on multistep forecasts (if you average the ...
4
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1answer
2k views

Time series forecasting using Gaussian Process regression

I used Gaussian Process Regression to predict a time series, what I have is sensor's readings that come every hour ( I have data for about 3 years) I chose the periodic kernel function mentioned here [...
4
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1answer
1k views

ARIMA modeling white noise probabilities vs. residual autocorrelation/PACF

I have moderate understanding of statistics and time series analysis. I trying to forecast a weekly time series with lots of outliers and trend shifts. After correcting all of the outliers, I'm left ...
4
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0answers
197 views

Comparison of estimation techniques for ARIMA model

I'm a math graduate student with not much knowledge in statistics. I could note that we have different techniques to estimate ARIMA parameters for a time series: using Bayes's Theorem, maximizing the ...
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2answers
467 views

Method for quantifying intervention effect in time series

How can the magnitude of an intervention be quantified in a segmented time series regression? I am attempting to replicate the methodology of Decline in pneumonia admissions after routine childhood ...
3
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1answer
748 views

Intuitive explanation of state space models

Having looked into options for modelling and forecasting a financial time series based on mixed frequency data, I came across state space models, which seems worth exploring. I've however been ...
2
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1answer
44 views

What is the meaning of an autoregressive parameter greater than one? [duplicate]

I have created a AR(2,1,0) model with the first two parameters equal to -1.08 and -0.33. I understand that a autoregressive parameter equal to 1 implies non-stationarity and a random walk process so I'...
2
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2answers
964 views

Flat ETS forecast of clearly increasing time series

I have a simple time series of one hour intervals: ...
2
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1answer
97 views

Prediction interval, forecast error for a function of a forecast

I have two variables $X$ and $Y$. For each variable I created a forecasting model (using time series) and estimated $X_{t+1}$ and $Y_{t+1}$ and the prediction interval and the error for each. I have ...
2
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1answer
1k views

Auto.arima choose between lots of regressors

I have to forecast data with two seasonality with ARIMA. I find that I have to use a code like this: ...
2
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1answer
6k views

How to work with index numbers?

I have Index numbers of Infrastructure industry. The base year for the first ten years i.e is 1993-94 = 100 and for the next ten years is 2004-05 = 100 My question is - How to work with index numbers ...
2
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1answer
58 views

What methods are available for forecasting with a sample of the data

In predictive analytics, specifically forecasting, what methods are available for getting the same predictive accuracy with $n$ (a sample of the data) which would be achievable with $N$ (all of the ...
2
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0answers
565 views

Comparing non-nested models with out of sample likelihood

I recently read a paper in which the authors claim that in order to compare the forecasting performance of two non-nested models, models A and B, a valid procedure is to fit models A and B on the same ...
2
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1answer
355 views

Given this time series, what statistical methods would be used for description and forecasting?

These static cumulative default rate tables and charts come from this public report published by a credit rating agency. Basically, you take all the loans originated in a period of time (a "vintage")...
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1answer
4k views

How to get in-sample forecast for ARIMA model in R? [closed]

I am using the code below: ...
2
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1answer
2k views

Standard errors of the fitted values of a time series regression

I really want to understand how the math is working here. I am trying to get the standard error of the fitted values for a time series regression model. In the non-time series regression, I know I can ...
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3answers
206 views

Combining expert estimates

I am trying to work on a process to improve how how well my team estimates. I want to look at using some statistics to help out and embrace the uncertainty in how we estimate tasks. If I have a group ...
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2answers
946 views

Should I adjust a Time Series dataset using X-13ARIMA-SEATS before running forecasts algorithms?

This question is sort of a follow up of this great thread. I have a Time Series Analysis project in which I have to create a model to predict new values given historical univariate data using R. My ...
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0answers
193 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 ...