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

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How to perform a simple smoothing forecast for next 12 months (using forecast package in R)

I currently have timeseries data (of gold prices) and I am trying to use a simple smoothing forecast to estimate gold prices for the next 12 months. I am not sure what function to use to accomplish ...
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34 views

Forecasting daily visits using ARIMA with external regressors

I have daily visitors data for the last 10 years. I want to do some basic tests like which is the busiest day, which is the busiest month, busiest week etc. I used ...
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5 views

trying to figure out how to make a suggestion given some input

I want to be able to express as a value (say 1-10 as an example), the strength of a suggestion that a person should do X tommorow. The rules are they should only do X in any 6 consecutive days out of ...
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1answer
61 views

Problems with time series prediction

I got a question about modeling time series in R. my data consist of the following matrix: ...
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1answer
131 views

R Time Series Forecasting: Questions regarding my output

I'm working on a forecast for the following data: ...
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2answers
44 views

Combination Forecast - Which models to pick?

Combination Forecasting can be produced by simply averaging different forecasts or employing more complex techniques (see Makridakis, 1989; De Gooijer and Hyndman, 2006; Goodwin, 2009; Pesaran and ...
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21 views

Getting Negative Forecasting Values [duplicate]

My data set in R contains the values like a b c 15 30 15 10 40 19 19 10 41 40 25 27 I have used the formula ...
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1answer
33 views

Providing 1 year monthly data (12 points), how to forecast next month

I got an interview question: Providing 1 year monthly data (12 points), can be traffic, product consumption, etc. How to forecast next month? I am confused. This question doesn't looks like a time ...
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24 views

Holt-Winters optimal parameters with gradient descent

Can we use gradient descent in order to find optimal alpha, beta and gamma for Holt-Winters model? And more generally, are there any academic works that suggest methods for finding optimal values for ...
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10 views

Conditional Expectation for Forecasting Intervention Model

William and Wei: Time Series Analysis Univariate and Multivariate Methods, Second Edition, page 90, gives the conditional expectation for $Z_{n+l}$ ($l$ step forecast of $Z_n$): $$ \hat{Z}_n(l) = ...
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30 views

root mean square error in forecasting

I have to use ARIMA model to forecast real prices of aluminium and copper in eviews. I have to do in sample and out of sample forecasting. my data set is annual from 1960 till 2014. I have selected a ...
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12 views

what is encompassing or nested models in forecasting?

I would like to ask what encompassing or nested models in forecasting means. I have a set of forecasts. A group of it is forecasted half hourly, so I have forecasts done a half an half an hour ago, ...
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1answer
28 views

How to align two seasonal time series

I am trying to decompose a time series using Holt Winters method and use it for forecast. I am trying to do this for weekly data of last 25-26 months. The challenge is that the dates of the seasonal ...
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1answer
30 views

Saving data into data frames in while loop for forecasting [closed]

I want to automate the forecasting procedure for a data set that I have. I have a three years of daily historic data and I want to use 2 years as test data and one year as train data. I want to have ...
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2answers
161 views

Reconstruction of Species Distribution based on poorly-sampled data

cross-posted to Signal Processing, World Building, and Biology Stack Exchange Problem: After reading a series of fantasy novels, I noticed that the biosphere in that world made no sense. To clarify, ...
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20 views

Interpreting tbats seasonal results for looking for the type of seasonality

Using tbatsfunction in R to look for seasonality. I test the seasonality for weekly and every 10 days and both have seasonality. ...
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1answer
128 views

Predicting the growth of traffic on a web site: regression or time series?

I've got a small website and I'm investing a lot of efforts on it. The traffic is growing but still very low. I've studied engineering but my knowledge of statistics is basic. I have put the last 70 ...
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20 views

Reorder point with stochastic lead time and demand

I'm trying to determine the optimal reorder point for some products. The reorder point must be greater than the demand during lead time a % of the times that I should determine, let's say 95%. ...
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2answers
31 views

arguments of length zero error with very similar code while forecasting

When I forecast from a linear Regression model in R using the following code, I get an arguments of length zero error , which I understand as a null pointer: ...
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21 views

Forecasting with use of PCA variables as independent and one ternary dependent variable in R

I'm having trouble in taking a direction of my research project. I have independent variables that are commonly used as economic indicators and I want to include variables/indicators that are not ...
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23 views

unable to perform holt winters forecasting on time series data

I am trying to perform a holt Winters forecasting for future dates in python. There is a working code but it only predicts one point ahead so at the end of the series, I only one more point for the ...
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1answer
52 views

ARIMA: How to interpret MAPE?

I am using the forecast package in R to generate an ARIMA model for my data. I started with the auto.arima function for a try and got a ARIMA(1,1,2) model. ...
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1answer
66 views

Can a forecast that reaches further into the future be less uncertain?

In Austrian television there is a weather show that gives temperature forecasts for the coming 15 days. They usually also provide uncertainty bands around that forecast which naturally makes the ...
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33 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 ...
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37 views

What is the best lag length for auto correlation?

I am doing a monthly rainfall forecasting model. I have monthly data from 1998 to 2012. I found in previous research that they have used partial autocorrelations and stepwise regression as an input ...
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1answer
35 views

How to validate random walk model

I am studying ARIMA models and find it hard to validate the model in terms of "it's a good, useful model" and "I shouldn't use that model for prediction". So at first I started with the easiest ...
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1answer
27 views

Time Series Hold Out Data not used to build model

It is my understanding that if one wants to build multiple time series models on a time series that goes from 2000 to today (2015) monthly; and one wanted to use that information to forecast 3 months ...
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42 views

Time Series using STS( Basic Structural Model)

I am using Basic Structs to forecast my time series. My forecast is exactly overlapping my data. I am sure no model can predict with 100% accuracy. I know I am missing something, can someone point me ...
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14 views
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40 views

Timeseries forecasting (Cointegration)

I am trying to forecast commodity price fluctuations in a small dataset. The data I am using is here . Does my data have seasonality and Trend? Can someone explain me how to decide that? If my ...
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37 views

How to use minor component analysis to forecast time series?

I would like to forecast a time series based on minor eigenvalues of the autocorrelation matrix. But I seem to be doing something wrong. I have the following steps implemented in MATLAB, but the ...
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422 views

Timeseries analysis procedure and methods using R

I am working on a small project where we are trying to predict the prices of commodities (Oil, Aluminium, Tin, etc.) for the next 6 months. I have 12 such variables to predict and I have data from ...
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100 views

STL + Random walk failing

We have four months of data (10 minute interval), this seems have nice pattern (at least for eye ball). We are using STL to decompose the time series and apply "random walk" to project next month ...
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19 views

error for using forecasting models inside a loop in r [closed]

I intended to automate the process of finding forecasts for every 48 hours for an hourly set of data. I simply want to read 3 years of historical data, fit a forecasting model to that and provide ...
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25 views

Questionable Output from Time Series Forecast Using MSTS and TBATS from R forecast package

Using historical daily order totals, I'm wanting to forecast the totals of the next 7 days. It's known in my field that these totals fall subject to weekly and yearly seasonal trends. Called ...
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7 views

Extract ETS method used for automatic forecasts of hierarchical time series with hts package [migrated]

I'm trying to extract the ETS method that is automatically chosen when we apply the forecast function to an hierarchical time series using the hts R package. When I look in the structure of the ...
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1answer
75 views

How to score predictions in test set taking into account the full predictive posterior distribution?

I have three predictive models (regressions) which parameters are estimated by Markov Chain Monte Carlo. Predictions are made over a test set of size $N$. Since I compare the models under different ...
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43 views

Incorporating intraday data into end-of-day forecast

my target variable is observable intraday but I am interested only in EOD forecasts. I will denote the variable $\ y_{D,24}$ as the reading of interest for day D is ...
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2answers
58 views

Let's talk sales forecasts - integrating a time series model with subjective “predictions/ leads” from sales team

I've learned a lot about time series forecasting this previous year, but one thing that's still a bit lacking in terms of a formal system is integrating a future sales projection into an existing time ...
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27 views

Multivariate stochastic time series forecasting

I have a multivariate time series like this ...
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24 views

best way of univariate prediction for sparse data

I have a client who has sparse hourly data (by sparse I mean there are too many hours with 0 calls). I used TBATS in R to forecast hourly data for them. Regardless of the point forecast, the actual ...
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27 views

Arima Models Diagnostics

I'm doing a forecasting using seasonal ARIMA method. I'm using astsa package in r and I'm testing two models that I can't decide which one is better to use than the other The ACf and PACF for the ...
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48 views

AIC versus cross validation in time series

I am interested in model selection in a time series setting. For concreteness, suppose I want to select an ARMA model from a pool of ARMA models with different lag orders. The ultimate intent is ...
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25 views

Prediction intervals for mixture models for time series forecasting - is it really an average of the prediction intervals of the averaged models?

I'm trying to find out how to do forecasting with a mixture model (averaging the forecasts of an ets, an arima and an ...
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45 views

Diebold Mariano test for multiple forecasts in R

I am trying to do Diebold Mariano test for multiple forecasts. How do you implement this in R? Thanks a lot.
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14 views

Multi-step ahead forecasting with generalized additive models

I would like to build forecast models using generalized additive models (GAM) with AR(p) correlation specification and explanatory covariates, using similar methods to those described in this blog ...
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12 views

Forecasting hierarchical time series with different model for each bottom time series?

I have univariate time series data for each country of the world. I am interested in forecasting at both the global and individual-country levels. Although the value being measured is the same, the ...
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52 views

Where do you find info about which predictive distribution an algorithm uses for forecasting?

I am trying to fit a mixture model to a time series in order to make forecasts. I'm told that this is quite straightforward as long as the predictive distributions used by the component algorithms ...
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1answer
25 views

One-Step ahead predictive likelihood for time series forecasting

I am still new to Bayesian forecasting, so I am hoping to get some clarification on a simple concept (by the sounds of it). Suppose that we are interested in forecasting some time series one-step ...
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1answer
54 views

Issues in auto.arima algorithm when using external regressors and outlier correction

auto.arima is an automatic arima modeling function in forecast package in R that uses information criterion(example: AIC/BIC) to ...