Questions tagged [forecasting]
Prediction of the future events. It is a special case of [prediction], in the context of [time-series].
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Accuracy of Volatility Forecast
I understand the basic concept of ARCH/GARCH models and the basic mathics behind it. That is, one models the "volatility" of a time series, i.e. the residuals of a time series describing ...
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Predict time series of parishable and seasonal product just with 1 year dataset
I want to predict the amount of demand for several types of fruit in a number of market with LSTM model.$ $
But I have a big problem, that I only have the dataset of one last year and because of that ...
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How to make sense of rescaling time series of counts?
I'd like to forecast time series of counts : sold items. Each time series represents monthly sales.
I also believe that there are clusters within the series, with low, medium and high count items. ...
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Predicting the Residuals of a Forecast Model
I have just read a paper [1] in which the authors try to forecast risk of some variable (earnings in this case) by deriving dispersion measures via forecasting quantiles of the respective variable, i....
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13 views
Time-series prediction shifted from the actual
I am trying to predict the AAPL stock price 5-days out from today's closed. I have included technical features like 20, 50 and 200 days moving averages in the price ...
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6 views
Forecasts combination via weights based on normal distribution
I am working on combining forecasts. I thought of calculating the weights based on normal distribution. This latter is fitted on the past values of the time series.
My issue is, should the weight be ...
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1answer
58 views
How can I calculate the parameters of a MA time series model?
I am new to Time Series Analysis and I have problems understanding the MA-model (opposed to the AR model). I read many webpages about it and it is either said that MA is a linear regression with past ...
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1answer
23 views
ARIMA model with delay in fitting and constant prediction
I am trying to use ARIMA (Python, statsmodel) on the following time series, values are collected with a weekly frequency:
...
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1answer
23 views
How does forecast::tsclean() detect outliers in R?
Does it use a particular z-score?
I know that it does apply STL.
My data is seasonal, and had quite a few outliers, so I am just wondering how exactly it determined whether a particular data point is ...
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24 views
Can I hybridize between ARIMA model and exponential smoothing?
I have a time series that stabilized at the first difference (d=1) and the model was ARIMA(0.1.0), as I know it is a model that does not really predict.
In this case I relied on hybridization as ...
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1answer
23 views
Time series analysis of daily temperature data in R
I am pretty new to the topic of time series analysis and I am trying to use the package "forecast" on daily temperature data to predict the daily temperature in the future. To be precise, I ...
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1answer
13 views
Bayesian methods for multi-day time series prediction
I have been looking at recurrent neural networks and LSTM models for time series, and it is interesting that they can predict multiple days ahead. For example, I can take inputs of 100 days and ...
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35 views
Forecasting the spikes in time series river gage data
I have an idea for a personal project knitting together river level gage data with weather data sets to look at how upstream and surrounding area rainfall events affect river levels. I would probably ...
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31 views
Forecasting Quarterly Time Series Data?
I've gotten very confused reading all the articles about forecasting time series data with seasonality on Medium and other sources. It seems that many provide useful background and importance of ...
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1answer
119 views
ARIMA Model Changing With New Data
I developed an ARIMA model with errors (https://robjhyndman.com/hyndsight/arimax/) to forecast the GDP growth of a small region. The issue is that the GDP values of past quarters and years change ...
