Finding Test Statistic Thresholds Using Simulation and Model Fitting with an Application to Radiation Detectionfalse alarm probabilitylocal regression smoothingSPRTtype I errorTo evaluate the performance of the sequential probability ratio test (SPRT) for radiation detection, we present an algorithm based ...
We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more...
In this context, the sampling distribution of a test statistic defines the probability for ranges of values. Thesignificance level(α) specifies the probability that corresponds with the critical value within the distribution. Let’s work through an example for a z-test. The z-test uses the z ...
A cosinor analysis of the CRT can be used to extract parameters that summarize the characteristics of the rhythm: the mesor (Midline Estimating Statistic Of the Rhythm), the amplitude (difference between the mesor and the peak or trough), and the acrophase (time of the peak) [233]. The...
In the context of cell signature selection, the performance of CimpleG was contrasted to other state-of-art methods, such as t-statistic, Elastic Net, Random Forests, Boosted Trees, and Neural Networks. Our results indicate that Elastic Net, which is broadly used for aging signatures [2],...
Although at the summary statistic level we did not replicate the lack of localisation information, we did find trials on which detection responses were correct but those for localisation were incorrect. We were therefore able to use these to investigate factors that might con- tribute to an ...
The predictive models with optimal parameters were applied to the test data for performance comparison and error analysis. The feature selection was performed on the training set to identify violence-related warning markers using the ten-fold cross-validation setting. A parsimonious model was then ...
Closely related to CHISQ.DIST is CHISQ.DIST.RT( ). This function returns the right-tailed probability of the selected chi-squared distribution. The first argument is the observed value of the chi-square statistic, and the second argument is the number of degrees of freedom. ...
Descriptive statistic. The topic specificity is a descriptive statistic rather than a performance metric; the ‘optimal’ specificity depends on the user’s preference and cannot be objectively measured. Although there is no objective optimum, the information provided by the metric helps in understanding...
Finding functional regulatory elements in DNA sequences is a very important problem in computational biology and providing a reliable algorithm for this task would be a major step towards understanding regulatory mechanisms on genome-wide scale. Major ob