In this paper, we consider spectrum sensing in cognitive radio networks based on higher order statistics. The kurtosis, a fourth order statistic, which is a measure of deviation from Gaussianity, is used as a detection statistic. An optimum threshold is set up based on the Neyman-Pearson criterion and analytical expression for upper bound on probability of miss is derived for a single pair of p...

We describe a multivariate, multilevel, pseudo maximum likelihood estimation method for multistage stratified cluster sampling designs, including finite population and unequal probability sampling. Multilevel models can be estimated with this method while incorporating the sampling design in the standard error computation. Design based adjustment of the likelihood ratio test (LRT) statistic is ...

The greedy search approach to variable selection in regression trees with constant fits is considered. At each node, the method usually compares the maximally selected statistic associated with each variable and selects the variable with the largest value to form the split. This method is shown to have selection bias, if predictor variables have different numbers of missing values and the bias ...

The master equation described by Badri Krishnan et al. [1] for the time-frequency pattern using the F-statistic is studied in context of the Chebyshev polynomial modified spindown parameters for the case of gravitational wave (GW) pulsar signals. The Chebyshev polynomial method enables an analytic and numeric evaluation of the Fourier transform (FT) for both the non-demodulated and F-statistic ...

To analyze the reliability of a complex system described by minimal paths, an empirical likelihood method is proposed to solve the reliability test problem when the subsystem distributions are unknown. Furthermore, we provide a reliability test statistic of the complex system and extract the limit distribution of the test statistic. Therefore, we can obtain the confidence interval for reliabili...

Statistic language models obtained from a large number of training samples play an important role in speech recognition. In order to obtain higher recognition performance, we should introduce long distance correlations between words. However, traditional statistic language models such as word n-grams and ergodic HMMs are insufficient for expressing long distance correlations between words. In t...