Prediction of the future events. It is a special case of [prediction], in the context of [time-series].
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0answers
9 views
Forecasted values by auto.arima not matching with manual calculations
I have build an ARIMA model using auto.arima in R and using it for one step ahead prediction. But when I match the predicted value of R with the predicted value ...
1
vote
2answers
33 views
Moving Average, Exponential Smoothing, and Random Walk for Forecasting
I would like to confirm my understanding. Is it true that a (simple) exponential smoothing model with alpha (smoothing constant) = 1 is the same as MA(1), which is in turn the same as a random walk ...
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0answers
15 views
Hyndman - Forecasting with Exponential Smoothing - Infinite vs Finite Start-up
In Hyndman's textbook, "Forecasting with Exponential Smoothing - the State Space Approach", in chapter 3, it was mentioned that most of the chapters in that textbook deal with the assumption of Finite ...
3
votes
0answers
12 views
How to account for remainder in forecasting?
I've done an STL decomposition of a time series. While trend accounts for major variations, remainder has a "cyclical" setup.
I want to know what other forecasting methods I can apply to maximize ...
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votes
1answer
18 views
ARMA: modelling a time series with a bimodal distribution
I have a de-trended and de-seasonalized time series, and it's distribution is not gaussian (see distribution in Figure 1).
I tried modelling it with and ARMA model, but as we could expect, this model ...
1
vote
0answers
32 views
Using information about covariance between ARIMA models in forecasting
I'm interested in how to incorporate information about the covariances of related timeseries from multiple univariate forecasts into each forecast. The ultimate goal of this is to implement ...
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0answers
8 views
LSTM time series forecast with horizon 5
I want to build a forecast with horizon 5. Let's assume $y_t$ (normalised to [-1, 1]) has some autoregressive character and $N=100$.
For my training model I have $y_{91..95} = f(y_{1..90})$ where f()...
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1answer
22 views
Forecasting with VARs: Merge differenced forecast with original data in levels
I am using R and am trying to figure out how to merge some forecasts I've done via the vars package, back to my original xts data, which is in levels.
In previous work, I would have used only level ...
1
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0answers
23 views
Forecast interval for ARIMA and ARIMA-GARCH model with $d\geq 1$
I have a question connected with confidence interval calculation.
So, let's have a ARIMA(p, 1, q)-GARCH(P, Q) model with drift: $\phi(L) \omega(t) = \theta_{0} + \theta(L) \varepsilon(t)$, where $\...
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0answers
35 views
LSTM for time series forecasting bad performance
I am trying to design a neural network for time series forecasting using LSTM neurons.
I am stuck because the many different configurations that I tried so far are not performing well (actually they ...
-1
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0answers
19 views
Probability of a subjective event based on historical subjective data . Forecasting [on hold]
Lately i developed an ldea of understanding the behavior of kids in their childhood. I was wondering how kids are moulder into different adults in no time. So i created a problem statement based on my ...
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1answer
42 views
Time series with multiple features
I'm trying to design a DNN for time series prediction. I have time series data with 2 features. I would like to leverage on stacked LSTM layers due to it's powerful predicting capability. However I'm ...
2
votes
1answer
42 views
Forecasting using ARIMA model and exogeneous variables
I have sales data for 7 years on a daily basis with breaks for the weekends.
I have a few questions
Should I aggregate it to a weekly or monthly level?
I would like to forecast for 'h' steps ahead. ...
2
votes
2answers
41 views
How can I explain a time series forecast?
Lets' say, I have built a time series model that can predict daily product sale. Now, for example, time series prediction indicates that sale will drop tomorrow. How can I explain the forecast? Using ...
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votes
2answers
22 views
SMC (Particle Filtering) code
Does anyone know where I can find particle filtering code for R? In particular I'm looking for code for filtering a forward-rate curve.
