In a previous paper, it was shown that parameter-effects nonlinearities of a nonlinear regression model-experimental design-parameterization combination can be quantified by means of a ...

We propose new approaches for choosing the shrinkage parameter in ridge regression, a penalized likelihood method for regularizing linear regression coefficients, when the number of observations is ...

The second part of this example uses the parameter estimates to score a new data set. The following code produces Output 57.2.4 and Output 57.2.5: /* The FITNESS2 data set contains observations 13-16 ...

This example shows how to build a menu system that enables you to perform nonlinear regression from a menu. Six modules are stored on an IML storage disk. After you have stored them, use this example ...

Abstract: This paper proposes a compensation strategy of the unwanted disturbance voltage due to the inverter nonlinearity employing an emerging learning technique called support vector regression ...

Abstract: In the OFDM-based digital terrestrial broadcasting systems, impulsive noise is a significant factor affecting communication quality. A prominent method to suppress impulsive noise is to ...