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

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How can a forecast evaluation measure consider the forecast uncertainty?

An Introduction Assume that $\text{g}_{h}^{m}(\mathcal{X}_T)$ is the $h$ period ahead forecast of $m$, a specific forecasting procedure or model, using information available up to time $t=T$ and ...
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13 views

Create weekly forecast of sales data and see impact of weather data on product movement

I am new to R and analytics. I am trying to create weekly forecasting model. Additionally , I have been asked to see if following components impacts product movement : Weather data ( Mean ...
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11 views

Dynamic regression linear models in R

I have a question regarding Dynamic regression linear models. I wonder if it is possible to implement a MLR model (in R) using 'lm' and creating lagged values of predictors and dependent variables. ...
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10 views

Recursive function that operates on its own preceding output [on hold]

I have the price for a particular baseline year (in this case for 1993), and the multiplication factor for all the years. Using these known multiplication factor, I want to compute (project) price for ...
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17 views

What is the difference between GAS ( Generalized Autoregressive Score) model and a GARCH?

I am trying to analyze some data about Brent Oil volatility. So far I have managed to fit a GARCH(1,1) model and an EGARCH. However, someone has recommended to use a GAS model, Generalized ...
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7 views

Measuring the effect of weather on retail sales

I'm currently working on modeling this as an ad hoc. Sr mgmt want to know how much of our sales growth during the year can be attributed to weather. I chose to investigate "weather" as temp & ...
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9 views

How to define holt winters model for forecasting using output R [on hold]

My research is comparing between SARIMA & HoltWinters multiplicative. I got confused when I tried to define forecasting model for HoltWinters multiplicative, because I thought model SARIMA and ...
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15 views

forecast nonstationary time series and test significance parametrs of AR model

I have a non-stationary time series, wich i want to fit with AR model, first of all i need to take difference wich make my TS stationary, then i see on PACF plot and see that difference number 4 is ...
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20 views

Time Series Forecasting, Log or non-Log

I have read that you should use log transformations when the fluctuations on your data are increasing over time, but what do you do if the fluctuations level out over time? A plot of the time ...
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28 views

Analysis of Time Series Data in R [closed]

I am attempting to use the 'forecast' package. I have a series of 54 monthly observations, read from a CSV file, and converted to a time series. Here is the raw data: ...
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8 views

How to deal with continuous variables with NULL values in prediction tasks?

I'm currently working on a machine learning project, trying to predict the expected revenue from a specific user. I have a long list of features that display the date when the user first performed a ...
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1answer
8 views

exporting from R objects of class “gts” “hts” [closed]

I am trying to save my forecast of class "gts" "hts" from R into excel but I get an error in R - "cannot coerce class "c("gts", "hts")" to a data.frame". Thank you, Despina
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9 views

Reference for forecasting nonstationary variables

My goal is to extrapolate / forecast data up to 10, 20, 100 years depending on certain independent variables. Is there like a publication or a book that I could follow that specifically pertains to ...
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1answer
29 views

Time series analysis of electricity load questions

I have hourly data of electricity load (MW) that span 8 months (that is, 5760 data points). I also have predictions from a regression model for the same period. My goal is: to examine some ...
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0answers
7 views

Statistical Formula to determine intersection point between 2 variables [closed]

I have 2 datasets, Incremental cost and reach of an advertisement. I need to find the a point of spend after which the effectiveness of my reach decreases. In order words, my cost of quality ...
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2answers
19 views

Scaling predictors in ARIMA model

If a predictor in an ARIMA model has much lower magnitude than the variable you are trying to predict, then do you need to multiply it by a scalar in order for it to be an effective predictor in the ...
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11 views

Negatively Correlated Predictors in Arima Model

If a predictor is negatively correlated with a variable you are trying to forecast in an Arima model, will Arima pick up the negative correlation when you add the predictor in the xreg argument? Is ...
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5 views

Combining Lower Correlation Predictors to Create Higher Correlation Predictors

I'm working on an Arima model to forecast a given variable and so I'm looking in my data for variables with correlation to the variable I'm trying to predict, to add as predictors in the xreg ...
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40 views

How do I interpret ACF and PACF figures from a SARIMA model? [closed]

I have data about tourism arrival. the plot of data is this is result after first differencing So, what is SARIMA model for this problem?
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10 views

Analysing likelihood of a vote swing [closed]

Data : Votes = 4,477,942 Bellen=50.3 to Hofer=49.7 Difference= 0.6% 26,867 Bellen = 2,252,404 Hofer = 2,225,537 Votes non postal = 3,777,942 Bellen=48.1 to Hofer=51.9 Difference= 3.8% 143,561 Bellen ...
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1answer
51 views

Forecasting elections by using survey data (in R)

In advance: my sincere apologies for any incompleteness, lack of knowledge and general stupidity in this post. I am doing my ultimate best to be as complete and thorough as possible - but I ...
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14 views

ARIMA forecast with auto.arima() and xreg [migrated]

I have a time series data y with some external regressors x1,x2,x3. For this time serie I need to do forecasting over 5 years. I did the following. ...
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9 views

Refitting model Holt winters with Testing Data in R [closed]

I feel confused to refitting model Holt Winters with my Testing Data in R. Here's my model from my Training Data Is it okay using this method below to refitting the model with my Testing Data? ...
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22 views

Forecasting next value range based on variance and historical values

If I know next variance from GARCH(1,1) model, can I get $X_{i+1}$? For example: $$ \sigma^2_n = \frac{1}{N} \sum_{i=1}^n(X_i-\mu_i)^2 $$ where $$ \mu_i = \frac{1}{n} \sum_{i=1}^nX_i. $$ So $$ ...
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1answer
28 views

Forecasting beginner question, using regression and historical data

I'm new to forecasting, I wanted to forecast the rise or drop of data traffic considering the number of subscribers I have, I have data from different countires, I used linear regression to get a line ...
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3answers
120 views

Seasonality not taken account of in `auto.arima()`

I am having basically the same issue than in this thread, except one thing: The difference, in my case, is that my data is measured weekly and not daily, so the argument of a too high seasonality (> ...
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2answers
57 views

Forecasting with multiple predictors and with multiple seasonalities in R

I have half-hourly electricity data of several homes for a duration of one month. Also, I have ambient temperature at same sampling rate. Now, I need to make half-hourly forecasts using historical ...
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13 views

Parallel processing in ARIMA [migrated]

I have one month half-hourly data (48 readings per day). Using auto.arima() of R forecast package, I forecast the readings of ...
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55 views

How to improve a bad long-term forecasting of time series in common case

I have two time series $d_t(t)$, $d_c(t)$, where I'm modelling charge as a function of time. Lengths of time series, $N$ are equal to $101$ data points. For the $d_t(t)$ (test sample, short-term) the ...
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1answer
117 views

allocating degree belief to forecast value

We have a number of providers for a forecast of wind power generation per country per date. Values are forecast up to one week ahead. Forecasts may be compared with actual values of reported wind ...
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3answers
73 views

Forecast time series data with external variables

Currently I'm working on a project to do forecasting of a time series data (monthly data). I am using R to do the forecasting. I have 1 dependent variable (y) and 3 independent variables (x1, x2, ...
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1answer
31 views

Mention day-wise seasonality for forecasting in ARIMA using R

I have half-hourly electricity data of several homes for a duration of one month. This data is represented in xts time-series format. Now, I need to make ...
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1answer
19 views

Is there any statistical cost to adding further levels to a time series hierarchy from a forecast perspective?

For example, when using gts() and forecast.gts() in r, should I prefer a model of product category -> product OR product category -> product -> subproduct? What does it depend on?
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25 views

How does the forecast package compute prediction intervals?

I'm currently working with random walks with drift in R, I use the rwf formula from the forecast package and I wonder how the prediction intervals are computed. As I understand it, for the random walk ...
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1answer
13 views

Measuring forecasting risk of linear regression

I want to measure how much risk I take by forecasting something. I know I can measure the error and things like MAD, MSE, ...
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1answer
51 views

Trouble from Time series and Support vector regression (Overfitting problem)!

Why I select the SVMR because It has shown its great advantage in small sample learning and do not require stationary process. However, I have trouble doing support vector regression for a month. Even ...
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1answer
15 views

Using Holt-Winters formula, how do you choose which seasonality to begin your first forecast period with?

This is probably a pretty basic question but I'd like to understand how you choose a seasonality number for the first forecast period in a Holt-Winters model. If you need to forecast 8 months ahead ...
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23 views

Markov Switching Model Forecasting

Let's say I have the following Markov switching model: $$r_t = 1.36 + a_t$$ $$a_t = \sigma_t \epsilon_t $$ $$ \sigma_t^2 = \left\{\begin{aligned} &0.15a_{t-1}^2 + 0.82\sigma_{t-1}^2 &&: ...
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1answer
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ARIMA Time series forecasting in R, help on choosing adequate model

I am trying to create adequate time series model in R. I have doubt about adequacy. My data is year and total number of events: ...
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How to fit an appropriate SDE [closed]

Does any one know how we can fit an appropriate SDE to a time series data? how to understand which model will describe the model well? and then how to estimate its parameters? To be more specified, I ...
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24 views

Difference between comparing forecasts and models

I started out looking for a way to test the difference between MSPE between two models (Question here), when (thanks to @Richard Hardy) I ended up reading a paper of Diebold regarding the ...
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Using historic water flux data to detect the existence of leakage, where should I start?

This question is also linked to How to detect a relatively small level shift(leakage) in an hourly water flux time series in an area? which I asked a week ago... Background I've got a series of ...
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36 views

One Step Ahead with a forecast horizon of 25

I have 288 data points of the Wolf's sunspot data for the years 1700 to 1987. I need to predict one step ahead forecasts for a forecast horizon of 25. I kept the last 25 data points of the time ...
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23 views

Linear Regression for Forecasting: what are the risks?

I have a dataset containing financial data of multiple firms on 7 to 10 years. (yearly data). For each firm/variable i want to predict its value in the next two years. I don't have enough data (7 to ...
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11 views

Revenue Forecasting using Markov Chain or Queuing Theory?

I am trying to forecast revenue for a HealthTech giant that sales HealthTech Hospital Equipment like Ultrasound, Magnetic resonance, CT AMI etc. The nature of business is Build to Order, which means ...
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15 views

Is there a way to force seasonality from auto.arima [migrated]

With the forecast package, I have a time series that I would like ?auto.arima to automatically pick the orders but I would like ...
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1answer
32 views

ARMA errors and combining explanatory variables

Currently I'm working on forecasting the employee turnover of an organisation. To do this, I'm using a time series data of the employee turnover over the past 7 years, it is an annual data. To make a ...
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1answer
40 views

Time Series forecasting with useful predictor variables

I am playing with time series data related to a issue ticketing system. The system logs all open tickets at any one point and my task is to predict what the volume of open tickets will be in 5,10,15 ...
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9 views

forecasting with ratio

i have daily data about revenue and number of push notification sends. I am trying to predict revenue/sends by day. there is a day of week effect also and days may have different sends. For example ...
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27 views

Forecast the profits for the stores in diffrent locations [closed]

I have data set for stores as below about 700 rows for various store locations and below are columns ...