Coefficient-Based Regression with Non-Identical Unbounded Sampling

Jia Cai
2013 Abstract and Applied Analysis  
We investigate a coefficient-based least squares regression problem with indefinite kernels from non-identical unbounded sampling processes. Here non-identical unbounded sampling means the samples are drawn independently but not identically from unbounded sampling processes. The kernel is not necessarily symmetric or positive semi-definite. This leads to additional difficulty in the error analysis. By introducing a suitable reproducing kernel Hilbert space (RKHS) and a suitable intermediate
more » ... gral operator, elaborate analysis is presented by means of a novel technique for the sample error. This leads to satisfactory results.
doi:10.1155/2013/134727 fatcat:tdccsw6fsrerldlut6act7mvw4