Image detection under low-light-level conditions is treated as a hypothesis-testing problem in which the observations are modeled as a shot-noise process. Since computing the likelihood ratio for shot-noise processes is not feasible, the use of a one-dimensional test statistic obtained by filtering and sampling the observations is proposed. The filter is chosen to maximize a generalized signal-...

Cognitive radio is an autonomous transceiver that is continuously sensing the ongoing communication in its environment, it then starts the communication whenever it is appropriate. Therefore, cognitive radio helps improving the spectrum utilization of the overall communication system. However, without suitable spectrum sensing techniques, cognitive radio would fail. Hence, in this thesis we inv...

Interval estimation of the mean and quantiles of a lognormal distribution is addressed based on a type I singly censored sample. A special case of interest is that of a sample containing values below a single detection limit. Generalized inferential procedures which utilize MLE based approximate pivotal quantities, and some likelihood based methods, are proposed. The latter include methodology ...

In an effort to improve the small sample properties of generalized method of moments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilting estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We us...

BACKGROUND Likelihood ratios offer important advantages over sensitivity and specificity for characterizing diagnostic tests. They can capture the magnitude of abnormality of test results, whereas sensitivity and specificity require that the test results be dichotomized into positive or negative. This is an important advantage because many diagnostic tests are measured on continuous or ordinal ...

The likelihood ratio approach for DNA typing in criminal cases is described. It is shown how this approach uses both the sizes and pattern of discrepancies between the crime scene profile of fragment lengths and the suspect profile for quantifying the strength of the evidence. In contrast to the current match-binning approach, it avoids an initial decision about whether the two profiles match. ...

Focused on interpreting data as statistical evidence, the evidential paradigm uses likelihood ratios to measure the strength of statistical evidence. Under this paradigm, re-examination of accumulating evidence is encouraged because (i) the likelihood ratio, unlike a p-value, is unaffected by the number of examinations and (ii) the probability of observing strong misleading evidence is naturall...