Abstract: In this paper we provide a comprehensive study of statistical inference in linear and allied models which exhibit some analytic perturbations in their design and covariance matrices. We also indicate a few potential applications. In the theory of perturbations of linear operators it has been known for a long time that the so-called “singular perturbations” can have a big impact on sol...

The human immunode ciency virus (HIV) is the causative agent of the acquired immunode ciency syndrome (AIDS) which claimed nearly 30 million lives and is arguably among the worst plagues in human history. With no cure or vaccine in sight, HIV patients are treated by administration of combinations of antiretroviral drugs. The very large number of such combinations makes the manual search for an ...

Most published research findings are false according to Ioannidis. As social animals, we are attracted, sometimes irresistibly, towards accepting sensational positive results and inclined to dismiss the negative ones ---which may be just as important. We have also come to believe that the reliability of a result in medical research, including optometry and ophthalmology, should be expressed sol...

BACKGROUND As a result of reporting bias, or frauds, false or misunderstood findings may represent the majority of published research claims. This article provides simple methods that might help to appraise the quality of the reporting of randomized, controlled trials (RCT). METHODS This evaluation roadmap proposed herein relies on four steps: evaluation of the distribution of the reported va...

Selection bias is caused by preferential exclusion of units from the samples and represents a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized experiments and can rarely be detected in either experimental or observational studies. In this paper, we provide complete graphical and algorithmic conditions for recovering conditional probabilities from sel...

Selecting a threshold for the statistical parameter maps in functional MRI (fMRI) is a delicate matter. The use of advanced test statistics and/or the complex dependence structure of the noise may preclude parametric statistical methods for finding appropriate thresholds. Non-parametric statistical methodology has been presented as a feasible alternative. In this paper we discuss resampling-bas...

We introduce a model of two-sided statistical discrimination in which worker and firm beliefs are complementary. Firms try to infer whether workers have made investments required for them to be productive, and simultaneously, workers try to deduce whether firms have made investments necessary for them to thrive. When multiple equilibria exist, group differences are sustained by both sides of th...

Abstract. It is di cult to directly apply conventional significance tests to compare the performance of network classification models because network data instances are not independent and identically distributed. Recent work [6] has shown that paired t-tests applied to overlapping network samples will result in unacceptably high levels (e.g., up to 50%) of Type I error (i.e., the tests lead to...

Listening tests and Mean Opinion Scores (MOS) are the most commonly used techniques for the evaluation of speech synthesis quality and naturalness. These are invaluable in the assessment of subjective qualities of machine generated stimuli. However, there are a number of challenges in understanding the MOS scores that come out of listening tests. Primarily, we advocate for the use of non-parame...

Graph cut algorithms are very popular in image segmentation approaches. However, the detailed parts of the foreground are not segmented well in graph cut minimization.There are basically two reasons of inadequate segmentations: (i) Data smoothness relationship of graph energy. (ii) Shrinking bias which is the bias towards shorter paths. This paper improves the foreground segmentation by integra...