Moreover, it can be also considered as an extension of a simple, commonly used formula connecting MI and correlation coefficient \(\rho \), $$\begin{aligned} I^G(\rho )=-\log \sqrt{1-\rho ^2}. \end{aligned}$$ (3) It is derived by subtracting differential entropy of a ...
In all experiments, the models are trained with the Adam optimizer, employing a learning rate of 1 × 10−4 to minimize the likelihood of a cross-entropy objective. Additionally, we incorporate the ReLU activation function to introduce non-linearity into the networks. To mitigate overfitting ...
The latter might be reduced by amalgamating some categories, but this causes a loss of information. The extremely parsimonious discrete ARMA models by Jacobs & Lewis [15], in contrast, have a rather narrow scope of application, see the discussion in Section 2 for further details. Therefore, ...
The latter might be reduced by amalgamating some categories, but this causes a loss of information. The extremely parsimonious discrete ARMA models by Jacobs & Lewis [15], in contrast, have a rather narrow scope of application, see the discussion in Section 2 for further details. Therefore, ...
The latter might be reduced by amalgamating some categories, but this causes a loss of information. The extremely parsimonious discrete ARMA models by Jacobs & Lewis [15], in contrast, have a rather narrow scope of application, see the discussion in Section 2 for further details. Therefore, ...