Questions tagged [mase]
The Mean Absolute Scaled Error (MASE) was proposed by Hyndman & Koehler (2006, *International Journal of Forecasting*) as a scale free accuracy measure for point forecasts. It is defined as the ratio of the MAE to the one-step MAE achieved *in-sample* (this is frequently gotten wrong) by a simple benchmark method (often the naive random walk forecast).
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Seasonal Time Series Forecasting and MASE
I am creating a a number of forecasts for sales at various levels of data aggregation, based on the properties of the products (eg. is it in a bottle or a can). I plan to create multiple models and ...
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Diebold-Mariano test for one-step forecasts using Mean Absolute Scaled Error
This is my first time doing time series forecasting, so I am sorry for any inconsistencies in my question. But I have two different models that I want to compare. On Wikipedia, I read about Mean ...
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Is it ok to select models using MASE and present the metric to client area as MAPE?
My question follow this one.
Metrics such as MASE and MSE have better properties than MAPE.
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Understanding MASE and sktime implementation
Sorry, but after reading the Hyndman's paper here I don't understand a couple of key points.
The term "in-sample"
The implementation in Python using sktime
Regarding the first point, I ...
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Why is my MASE systematically equal to 1?
Hello I am trying to calculate the MASE of a store at hourly level. My questions are below:
If I sum up the different values, it sums to 24 (number of hours) and the average comes to 1. What am I ...
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How to calculate MASE based on tsCV output in R?
I have a large number of time series with different properties, and applied tsCV() function to them based on different models. Now I need to compare the forecast accuracy based on tsCV output. But I ...
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Why can't I reproduce the MASE of a time series manually as in done in the Fable package?
I am trying to produce the Mean Absolute Scaled Error (MASE) for a custom time series model to compare its performance in forecasting several indicators with different units. I wanted to check my ...
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Model performance in time-series forecasting with some outliers
I'm creating forecasts for products where some of them have large seasonal spike during times like Christmas and/or Easter but relatively low sales volume on other times. For this particular product ...
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Did I calculate the non-seasonal Mean Absolute Scaled Error (MASE) correctly?
This is the formula:
Here is the link to page in the book. I am not confident I am interpreting the formula correctly. Below is my data:
I calculate the non-seasonal MASE to be 1.125. Is this ...
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Interpretation of scaled error measures
can someone give me an explanation on how one would interpret the result of a scaled error measure.
For example the Mean Absolute Scaled Measure (MASE). The numerator is the mean absolute error and ...
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Out of sample MASE
When calculating the MASE, the original paper suggests using the in-sample naive forecast error for scaling of the out of sample forecast error.
When i use the the MAE generated by a naive forecast on ...
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Is there any standard / criteria of good forecast measured by SMAPE and MASE?
I have built a forecasting model for a company. Since it is dedicated to practical usage, I prefer to use the relative error parameter (like MAPE, SMAPE, & MASE) as a measurement for my model ...
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Computing aggregated MASE for multiple time series
I think I understand how MASE works when I have a single time series. But what if I have several, for which I want to obtain an overall accuracy measure?
It's straightforward to compute an aggregate ...
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R - How to create a forecast object from a pre-defined forecast, in order to apply accuracy() for MASE result
I am working with a forecast which has been created by Prophet. I would like to apply accuracy() to return the MASE after identifying this as the best accuracy measure for multiple forecasts, and will ...
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Do you clean the data before calculating MASE (Mean Absolute Scaled Error)
The denominator in the MASE calculation for seasonal data is the MAE of the seasonal naive forecast calculated in-sample.
Is it common to do imputation before calculating the seasonal naive MAE or ...
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