Structural break detection method based on the Adaptive Regression Splines technique

Intrusion Detection Systems Using Adaptive Regression Splines

Past few years have witnessed a growing recognition of soft computing technologies for the construction of intelligent and reliable intrusion detection systems. Due to increasing incidents of cyber attacks, building effective intrusion detection systems (IDSs) are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. In this paper, we r...

Multivariate Adaptive Regression Splines

Discussion: Multivariate Adaptive Regression Splines

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].. Institute of Mathematical Statistics is collaborating wit...

Spatially Adaptive Bayesian Regression Splines

In this paper we study penalized regression splines (P-splines), which are low–order basis function splines with a penalty to avoid undersmoothing. Such P–splines are typically not spatially adaptive, and hence can have trouble when functions are varying rapidly. While frequentist methods are available to address this issue, no Bayesian techniques have been developed. Our approach is to model t...

Locally adaptive smoothing method based on B-splines

This paper presents a novel method for the edge-preserving smoothing of biomedical images. It is based on the convolution of the image with scaled B-splines. The size of the spline convolution kernel at each image position is adaptive and matched to the underlying image characteristics; i.e., wide splines for smooth regions and narrow ones for pixels belonging to edges. Consequently, the algori...