Circular local likelihood

Local Likelihood and Local Partial Likelihood in Hazard Regression

Local Likelihood SiZer Map

The SiZer Map, proposed by Chaudhuri and Marron (1999), is a statistical tool for finding which features in noisy data are strong enough to be distinguished from background noise. In this paper, we propose the local likelihood SiZer map. Some simulation examples illustrate that the newly proposed SiZer map is more efficient in distinguishing features than the original one, because of the infere...

Local Maximum Likelihood Multiuser Detection

It is well-known that the optimum multiuser detector achieves the global maximum likelihood (GML) detection in the entire set of hypotheses and several other iterative detectors such as the SAGE detector achieve the local maximum likelihood (LML) detection in the smallest neighborhood. In this paper, we generalize the local maximum likelihood detection into any size of neighborhood. The charact...

Local Power of Likelihood Ratio

Likelihood ratio (LR) tests for the cointegrating rank of a vector autoregressive (VAR) process have been developed under diierent assumptions regarding deterministic terms. For instance, nonzero mean terms and linear trends have been accounted for in some of the tests. In this paper we provide a general framework for deriving the local power properties of these tests. Thereby it is possible to...

Local Circular Law for Random Matrices

The circular law asserts that the spectral measure of eigenvalues of rescaled random matrices without symmetry assumption converges to the uniform measure on the unit disk. We prove a local version of this law at any point z away from the unit circle. More precisely, if ||z| − 1| > τ for arbitrarily small τ > 0, the circular law is valid around z up to scale N−1/2+ε for any ε > 0 under the assu...