Forecasting involves estimating the value or distribution of a random variable which has not yet been observed.
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2answers
83 views
Overfitting when using corrected AIC for model selection
I am using the corrected AIC to select the lag order in a simple AR(p) model. I chose the the AICc since my sample is fairly small (n=135). The AICc minimal model is the AR(15). To me it seems like an ...
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1answer
73 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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15 views
In R, how to add a one-step-ahead forecast to a timeseries, using nothing but the forecast package? [duplicate]
I am wondering if its possible to add a one-step-ahead forecast to a timeseries, using nothing but the forecast package in R?
To avoid lookahead bias, this would involve running ...
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1answer
37 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 ...
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2answers
62 views
State space models for time series forecasting
I am new to time series forecasting and have been slowly working my way through the different approaches available. I've so far mainly been using ets and arima models available in the R forecast ...
0
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1answer
34 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? ? ...
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1answer
43 views
when to aggregate when time series forecasting
I have a some historical sales data for various product SKUs, including category information ("department" "category", "subcategory"). I want to use this to generate sales curve (a baseline forecast ...
6
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1answer
117 views
Can you compare AIC values as long as the models are based on the same dataset?
I am doing some forecasting in R using Rob Hyndman's forecast package. The paper belonging to the package can be found here.
In the paper, after explaining the automatic forecasting algorithms, the ...
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2answers
117 views
Forecast total for a year given monthly time series
I have a monthly time series (for 2009-2012 non-stationary, with seasonality). I can use ARIMA (or ETS) to obtain point and interval forecasts for each month of 2013, but I am interested in ...
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1answer
35 views
Exogeneous regressors in auto.arima and using them in forecast function in R
I'm trying to forecast a seasonal time series based on its historical values, and also two more time series (that are seasonal themselves.)
I'm trying to use an auto.arima, and I'm going to input ...
2
votes
1answer
73 views
How to forecast hourly data in R
I have hourly login data for a web site. Certain hours of the day for example between 09:00 and 12:00, there are heavy traffic on the site. I would like to forecast the hourly data for about one year.
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2
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1answer
43 views
What do error bounds in forecasting represent?
What do error bounds actually mean in forecasting timeseries? For example, when I get a forecast I get the 85% and 95% high and low error bounds. I can also set my own error bounds to be calculated ...
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0answers
30 views
Implementing an ETS and ARIMA forecast
I've been using the R Forecast package which I have used to create fitted ETS and Arima models. I can easily predict ahead within R using the Forecast package but need to be able to do prediction ...
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0answers
15 views
Is temporal aggregation helpful in demand forecasting?
I'm thinking in which situations considering the temporal aggregation in demand forecasting can be helpful, could you please help me if you have any idea?
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0answers
18 views
Temporal aggregation in Forecasting softwares
I know there are some softwares that use aggregation across individual items to produce the required forecasts, I was wondering if anybody tell me which Forecasting softwares(commercial or not) use ...
4
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1answer
111 views
Time Series Forecasting with Daily Data: ARIMA with regressor
I'm using a daily time series of sales data that contains about 2 years of daily data points. Based on some of the online-tutorials / examples I tried to identify the seasonality in the data. It seems ...
1
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1answer
24 views
How to accurately track the 75% quantile in a non-stationary timeseries?
I have a non-stationary timeseries with a mean (ยต) and standard deviation (SD) which both vary across time. The distribution of the timeseries is skewed, so the left and right sides of the ...
3
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1answer
73 views
Approaches to Forecasting with Daily Timeseries
I have just started to learn about forecasting. I thought it would be easy to create forecast models for a daily time series but have encountered a number of difficulties. Firstly most examples and ...
0
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2answers
75 views
Need a clear and simple auto-regressive model example
This may be hard to find, but I'd like to read a well-explained auto-regressive model example that:
uses minimal math
extends the discussion beyond building a model into using that model to forecast ...
2
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0answers
19 views
Predict binary occupancy vector from history of vectors
I have a set of binary vectors where each vector represents one day of occupancy in a house and consists of 48 elements (each element for 30 minutes of the day). Each element can be 1 meaning that ...
0
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0answers
27 views
How to specify newxreg in prediction model of ARIMA? [migrated]
I have fit the model below to my time series data. The xreg consists of a time vector that goes from 1 through 1000 and of 12 indicator variables (1 or 0) that ...
0
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0answers
20 views
forecasting export - methods
I have Product X Export data (time series data: year - amount) approx for last 10 years for my country and also Product Export data for Enterpise Y.
I am writing thesis. This would not be the main ...
1
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0answers
46 views
Forecasting of highly correlated time series
In time series forecasting using various models like AR,MA,ARMA, etc, we usually focus on the modeling of the data in the change of time. But when we have 2 time series that Pearson correlation ...
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0answers
18 views
Calculating error bars for Excel Linear Regression [duplicate]
I've ben sent a forecast of sales from a consultancy. It uses Excel's LINEST function, taking 4 factors that seem to have affected sales in the past, and used them to make a prediction.
How do I go ...
0
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0answers
24 views
SKU level disaggregation
I'm an MBA student currently interning with an Indian FMCG company. My project is on SKU level forecasting and I'm seeking your suggestions. I found the concept given in the Chapter "Family Member ...
0
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1answer
47 views
Can I use xreg with stl decomposition to handle moving holiday?
I am trying to decompose and forecast a weekly time series which is believed to be affected by moving holidays (e.g. Chinese New Year, which happens in different weeks of a year).
I would like create ...
2
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1answer
97 views
ARIMA forecast with seasonality and trend, strange result
as I am stepping into forecasting with ARIMA models, I am trying to understand how I can improve a forecast based on ARIMA fit with seasonality and drift.
My data is the following time series ( over ...
0
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1answer
48 views
One step ahead forecast with SEASONAL data collected sequentially
In this post it was asked how to do one step ahead forecasts using Arima form the forecast package. Now I'm using an example with hourly seasonal data and would like to do something similar but the ...
2
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0answers
79 views
Interpreting time series decomposition using TBATS from R forecast package
I would like to decompose the following time series data into seasonal, trend, and residual componenets. The data is an hourly Cooling Energy Profile from a commercial building:
...
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0answers
76 views
Simulate forecast sample paths from tbats model
Using the excellent forecast package by Rob Hyndman, I came across the need to not only have prediction intervals, but to simulate a number of future paths, given past observations of a time series ...
0
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1answer
54 views
MA on a non-stationary time series
All,
I have some data I would like to do some simple forecasting on. Its is non-stationary, looking at the time plot & from ADF & KPSS tests. After differencing I now have a stationary ...
0
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0answers
55 views
lag in prediction outputs in one-step ahead neural network autoregressive model
I am working on an ARX forecasting problem mostly using feed-forward neural networks in MATLAB. The functional model is of the form
$y(t) = f(y(t-1),...,y(t-n),u(t))$. My data is at half hourly ...
2
votes
1answer
109 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 ...
0
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0answers
20 views
Estimating Smoothing Parameters Simultaneously with Regression Coeffecients
I am developing a forecasting model that relies on a smoothed leading indicator. The indicator is the ratio of two smoothed series, and the forecasting regression equation uses a lagged value of the ...
0
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1answer
32 views
Is it possible to predict/forecast results of pairwise comparison matrices based on one or two initial samples?
I'm curious if it's possible to predict the results of a pairwise comparison matrix that will be sent out to 100 people based on the results of one or two filled out surveys?
The matrix has the ...
0
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2answers
88 views
Time Series Analysis and Forecasting
I am looking at ways to forecast monthly time series data over a larger geographic region. I have time series weather data (e.g., temperature, precipitation) from multiple stations, and the stations ...
1
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2answers
63 views
Time-series autocorrelations all positive
I've got 36 months of timeseries data, and eyeballing it, it has a linear trend upward. I wanted to do a little more than just eyeball it though. So I put together a correlogram of autocorrelation ...
2
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2answers
52 views
Forecasting the past?
More of a literacy question that stats, but I'm looking for correct terminology and the Google machine hasn't thrown anything up.
You have explanatory data and observed data for 2000-2010. You have ...
2
votes
1answer
46 views
Forecasting Extreme values
I am attempting to forecast "peak" values. I have a weekly data set ~10 years. I have weather metrics as explanatory variables. I am trying to produce a model that can accurately predict the peaks of ...
2
votes
1answer
56 views
What happens to an (AR)MA model when doing out-of-sample forecasting?
What happens to the error terms in an (AR)MA model when doing out-of-sample forecasting? As I understand it, when doing an in-sample fit, the estimate is simply the residual of the ground truth data. ...
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0answers
53 views
Bootstrap Prediction Intervals
My question concerns the construction of forecast prediction intervals using bootstrapping.
I have a 36 month time series, which I am using to perform point forecasts for the next 12 months using ...
0
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0answers
40 views
Calculating price elasticity from triple exponentially smoothed values
I have a time series which exhibits a linear trend and multiplicative seasonality, so I've smoothed it using Holt-Winters exponential smoothing. Now, I suspect some of the deviation between smoothed ...
-1
votes
1answer
47 views
Data set for forecasting [closed]
I am looking for a data set which can be used for ARIMA or any forecasting models. The data should be such that, over a period of time the range of inputs change i.e. the band of input data changes ...
2
votes
2answers
165 views
ARIMA forecasting
I have a data that I would like to use arima model to perform forecast. when I use auto.arima, my results does not seem right. When I change my arima order to c(1,0,1), numbers starts changing and ...
0
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0answers
61 views
How to update forecasts in an ARIMA model?
I am trying to forecast a series of monthly values. my data set is 100 values and I used 80 for building model and 20 for validating. My model is an ARIMA(1,0,1) and I am doing one step ahead ...
-1
votes
1answer
41 views
neural network for rainfall forecasting
I'm new to machine learning, and I have been trying to figure out how to apply neural network to rainfall forecasting. I have found resource related to my query, but I seem to still be a bit lost. I ...
0
votes
1answer
127 views
Forecasting using multiple regression
I have data in the form given below, and I want to perform forecasting using multiple regression. I found definition of multiple regression from this link: http://otexts.com/fpp/5/1/ . I have these ...
0
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2answers
279 views
Lewandowski algorithm demand forecasting
I came across the Lewandowski method of demand forecasting in JDA Demand. Please help me understand at a high level the methodology it uses. I found a paper by Robert Hyndman titled
"A state space ...
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0answers
77 views
Solution for long-term electricity prices forecasting
I'm trying to adopt a solution for long-term electricity annual prices forecasting (depending on past electricity prices, past oil prices, past consumption data, etc.)
I'm considering some solutions:
...
1
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1answer
42 views
Empirically validating a forecast distribution
I have a family of models that give me a forecast distribution for the next observation in a time series. So given observations $O_1, \dots, O_T$, I can calibrate the model and get a distribution for ...
