Forecasting involves estimating the value or distribution of a random variable which has not yet been observed.

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predicting Air cleanness (air pollution) in daily-basis

How hard it is to predicting the cleanness of air ? My friend is an agronomist, he is doing some research on some small plants. The plants are very sensitive to air pollution in urban area (need deep ...
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1answer
13 views

In triple exponential smoothing, what is the proper formula for recalculating gamma (seasonality)?

A pretty targeted but precise question -- In triple exponential smoothing (which there are many combinations of additive, multiplicative). What is the proper formula for calculating the new ...
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1answer
47 views

Hourly predictions using time series

I'd like to build a model based on time series. I have a dataset with records every 30 minutes for three months. What is the difference between modeling these data with the following kinds of ...
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23 views

Why does NSDIFFS (R forecast package) never show seasonality? [migrated]

I've been using the EViews statconn DCOM interface to loop a large number of series from FRED through the nsdiffs(test=c("ch")) function in the forecast package of R to examine what percent of them ...
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1answer
19 views

Selecting the best (or more suitable to the user/client) output from a set of forecasts

I have approximately 3000 products for which I have to forecast in every, say, 2 months. I have the code in place for different forecasting models such as ARIMA, forced seasonal ARIMA, STLF etc. Now ...
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14 views

Forecasting Unobserved Values from a Bayesian Multilevel Model

I'm interested in forecasting from a Bayesian multilevel logistic regression. The setup is as follows: $$y_{i,j} \sim \mbox{Bernoulli}(p_{i,j}) \\[0.5em] \mbox{logit}(p_{i,j}) = \beta_{0,j} + ...
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1answer
74 views

Are time series methods only good for forecasting?

Many time series methods are oriented solely in terms of forecasting (e.g., ARIMA). However, it seems like a growth curve modeling framework (i.e., random coefficient modeling) can do virtually ...
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26 views

Can you generate confidence intervals for time series ETS forecast components?

Suppose you fit a time series with the ets function from the forecast package in R: ...
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17 views

Predicting from Data [on hold]

I have a set of data, that contains ordering quantities for three days of the week, monday, wenesday and thursday. I want to know how to use these numbers to derive a pattern for ordering for each of ...
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2answers
36 views

Forecasting product of two time series with correlation

I am trying to forecast the product two time series. That is, given $\{x_t\}_{t=0}^{T-1}, \{y_t\}_{t=0}^{T-1}$, forecast $x_T\cdot y_T$. The two time series have minimal but nontrivial correlation ...
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55 views

Generalized Linear Models vs Timseries models for forecasting

What are the differences in using Generalized Linear Models, such as Automatic Relevance Determination (ARD) and Ridge regression, versus Time series models like Box-Jenkins (ARIMA) or Exponential ...
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29 views

Multi-​​step fore­casts with­out re-​​estimation for weekly data [closed]

I am trying to replicate the code written by Prof. Rob on Multi-​​step fore­casts with­out re-​​estimation for weekly data. How to write the below code for weekly time series data? I have weekly data ...
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20 views

General forecasting formula for ARIMA(p,d,q)(P,D,Q)s

what is general forecasting equation for sARIMA(p,d,q)(P,D,Q)s.? I wrote this equation, can someone confirm if it is a correct one? $\overline{y}_{t+m}=\frac{ (\varphi_{1}y_{t} + ...
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14 views

MIDAS Forecasting in R, using midasr package

I am attempting to provide a forecast on yearly data using monthly data as a regressor variable via the MIDAS regression from the midasr R package. Here is my data: y is yearly data ...
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23 views

How can i do time series forecasting with missing data

I am relatively new to time series forecasting, I have worked previously with continuous data at regular intervals successfully, Now I have a data set with missing values, for example look at the ...
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1answer
62 views

R forecasting, flat forecast

I’m trying to produce a hourly, daily forecast for revenue in R. I set seasonal periods to 24, for 24 hours, and 365.25 for days in a year. I attached the fit vs actual plot and the forecast produced ...
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25 views

auto.arima prediction

I have this time series of call volume of a contact center. It is composed of 15565 points where every 48 points represents one day. I used 12960 points as training set for the auto.arima model. ...
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17 views

How to model and forecast spike cycles in a time series

I’d like to model repeating peaks of various periodicity of a time series as a curve. Here’s the general scenario: A device under measurement experiences reasonably regular voltage spikes every N ...
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1answer
46 views

Explain the croston method of R

I am using crost() function of R for analyzing and forecasting intermittent demand/slow moving items time series. I am having difficulty in understanding the ...
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2answers
45 views

forecasting sharp seasonal peak in time series

I have time series data on a daily level over the past 4 years. What is clear from examining past data is that there are two very clear peaks in the time series around the same time of year (they ...
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1answer
24 views

Prediction period is coming wrong in the HoltWinters in R

I am Using Holt-Winters model for the forecasting. Below is the way I am proceeding: ...
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2answers
23 views

General forecasting equation for ARIMA(p,d,q)(P,D,Q)s

what is general forecasting equation for ARIMA(p,d,q)(P,D,Q)s.? I wrote this equation, can someone confirm if it is a correct one? If not, can someone correct it? Thank you in advance! ...
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19 views

How to determine Forecastability of time series?

One of the important issues facing forecasters is if the given series can be forecasted or not ? I stumbled on an article entitled "Entropy as an A Priori Indicator of Forecastability" by Peter ...
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21 views

Principled way of combining time series with different spans and granularity into an econometric model

I want to forecast the price of something given various time series as inputs. The problem is that they are of different frequency (annual, quarterly, monthly, daily) and time periods (the more ...
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1answer
48 views

Time Series Forecast: Convert differenced forecast back to before difference level

I am using R and I need an easier way to produce forecasts of data at the original level based on forecasts using differenced data. The situation, in more detail, is this: I am using several ...
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21 views

Method of Forecasting

What is the difference between ARIMA and UCM(Unobserved Components Model)? I have checked in some PDF's stating that Coefficients vary over time, we use UCM. I am confused over here that coefficients ...
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1answer
143 views

Time-series forecasting (in C#)

I'm developing an app in C# (WPF) that amongst other things, it makes a time-series based forecast of sales (4-5 months into the future). I'm an industrial engineer so I'm not pro in statistics nor in ...
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4answers
87 views

Time Series for each customer

Is it possible to create Time Series Analysis for each customer? Say if have 100 customers and I wanted to predict how much amount they are going to spend next. I have done the Time Series for the ...
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52 views

fitting a model for time series data

Folks, I am working on time series traffic data where the waiting times are indexed over time, with 288 observations for 24 hour time period (interval of 5 minutes). I am trying to cleanse the data, ...
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57 views

R forecast from STL

I want to understand how forecast from STL function in R works. So, I am not giving any reproducible code here. Below is the procedure that I worked on time series I used STL decomposition on my ...
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22 views

Forecasting sales for multiple departments using external factors

I have got the weekly sales information for various locations for about 3 years.It has got information for 157 weeks.Also,I have got the probable external factors affecting the sales.I want to ...
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1answer
39 views

Forecasting Stock Prices in PHP [closed]

Has anyone implemented stock prices forecasting, using php only. Like we give data sets of 1 yr of open,high,low,close,volume and get prediction for next 15 or 30 days? One example I saw is here ...
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3answers
66 views

forecast using arima models

I am trying to predict values using arima(0,1,1). After doing predict(mod,n.ahead=5) (in R) am getting the same value for all ...
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which code to be used for forecasting arima model [migrated]

i am trying to forecast an arima model (0,1,1) in R studio. which function can i used to forecast the model?
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7 views

Preparing data for Superior predictive ability (SPA) test

Can anyone please let me know how to prepare data to compute Superior predictive ability (SPA) test in R? I am working on forecasting volatility in stock markets, the context is, 1) I used "rugarch" ...
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1answer
43 views

Is time-series an appropriate method to model data sampled at widely irregular time intervals ?

I am relatively inexperienced with data analysis. My question: Is time-series an appropriate method to fit trends to data sampled at widely-irregular time intervals such as forests of different ages ...
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36 views

One Step Ahead Forecasts Using Predict() in R

I just fit a model to a time series. I am now required to generate a 10-year extrapolation forecast of my model. My model includes a time term, a time^2 term, 12 seasonal dummies, and 4 lagged ...
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29 views

Selecting an appropriate VAR model

I would like to receive critical comments on an idea explained below. Suppose I have variables $x_1$ through $x_K$, and this is a time series setting. My aim is to forecast variable $x_1$. I know ...
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1answer
33 views

Optimization failure in HoltWinters [closed]

I am using HoltWintersto fit the exponential model on the data. The data shows trend as well as seasonal pattern.Getting the following error message: ...
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27 views

Forecastability and Coefficient of Variation

I'm trying to get a sense check here. When determining "forecastability" for sales data, I tend to use the CV. However, this is highly susceptible to seasonality and outliers. As such, I was ...
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575 views

Is it unusual for MEAN to outperform ARIMA?

I'm relatively new to forecasting so I hope this isn't a ridiculous question. I recently applied a range of forecasting methods (MEAN, RWF, ETS, ARIMA and MLPs) and found that MEAN did surprisingly ...
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34 views

Making a neural network model more sensitive to one of its several inputs

I am currently using neural network methods in R to model energy consumption (response) based on temperatures, previous consumption values and weekend dummy variables (inputs). Unfortunately, the ...
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23 views

Techniques for comparing two windows of data in a time series

I'm working on a small independent project in R, trying to make my own (very crude) forecasting method. The general idea of the component that is giving me trouble is trying to compare two windows of ...
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31 views

Training/ Test Data with Time Series Model — Forecast with Training Model, or with Model based on Full Data?

Okay, I have a couple books on time series forecasting, but perhaps I need to read a couple more. Here's my question. You want to be able to validate a forecasting model. So you split the data into ...
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1answer
43 views

R times series — correct use of forecast() and accuracy() in forecast package

Cross-posting this from Stack Overflow, because it's a bit of a stats/ technology cross-over. I'm relatively new to R and the forecast package I believe authored by Rob Hyndman. I'm having trouble ...
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2answers
129 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 ...
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50 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, ...
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32 views

autocorrelation in evaluating time series forecasts

I'm having some trouble wrapping my head around whether using Holt-Winters ETS or an ARIMA model for forecasting sales figures (which are highly seasonal). I'm been using R and the Forecast package ...
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20 views

VAR model for price forecasting in multiple time-series context. How to get “real figures” as forecasts?

Sorry for the rather long introduction, but since I was (legitimately) critizised for not explaining my cause and questions enough, I will do so now. I would like to conduct a (price)-forecast based ...
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2answers
80 views

Transfer function in forecasting models - interpretation

I am occupied with ARIMA modelling augmented with exogenous variables for promotional modelling purposes and i have hard time explaining it to business users. In some cases software packages end up ...