arma.muc

The MUC of a given model selection method with good performance will tend to arch towards the upper left corner. Moreover, the area under the MUC, marked as AMUC, can be used as a raw measure of uncertainty of uncertainty for the model selection method under examination. The larger the AMUC, the stabler the corresponding model selection method. Overall, we can decide which method has the best performance according to the shape of the MUC and the AMUC.

We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance not pay attention to the accuracy of prediction, but focus on model selection uncertainty and providing more information of the model selection results. And to estimate the model measures, we propose an simplify and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance focuses on model selection uncertainty and providing more information of the model selection results. To estimate the model uncertainty variance, we propose an simplified and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. Please see Li,Y., Luo,Y., Ferrari,D., Hu,X. and Qin,Y. (2019) Model Confidence Bounds for Variable Selection. Biometrics, 75:392-403.<DOI:10.1111/biom.13024> for more information.

Heming Deng

uotm

Uncertainty of Time Series Model Selection Methods

Heming Deng Developer

Sunan Gao Dev

arma.muc function

<dl><dt>method</dt>
<dd>Model selection method like "aic", "bic" and "aicc".</dd><dt>...</dt>
<dd>Others.</dd></dl>

Arguments

Plot the model uncertainty curve of time series model selection method. — arma.muc

<dl>

<dt>method</dt>
<dd>Model selection method like "aic", "bic" and "aicc".</dd>

<dt>...</dt>
<dd>Others.</dd>

</dl>

arma.muc: Plot the model uncertainty curve of time series model selection method.

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