We express some criticism about the definition of an algorithmic sufficient statistic and, in particular, of an algorithmic minimal sufficient statistic. We propose another definition, which might have better properties.

Inspired by the k-inversion statistic for LLT polynomials, we define a k-inversion number and k-descent set for words. Using these, we define a new statistic on words, called the k-major index, that interpolates between the major index and inversion number. We give a bijective proof that the k-major index is equi-distributed with the major index, generalizing a classical result of Foata and red...

The LMS-based adaptive order-statistic filters are presented in this paper. The adaptive Ll-filters as extension of the adaptive L-filter for two-dimensional filtering of noisy greyscale images is studied too. Their adaptation properties are studied by three types of noise, the additive white Gaussian noise, the impulsive noise or both, respectively. Moreover, the impulsive noise has the fixed ...

In this paper we derive a one-sample multivariate empirical Bayes statistic (the MB-statistic) to rank genes in the order of differential expression from replicated microarray time course experiments . We do this by testing the null hypothesis that the expectation of a k-vector of a gene’s expression levels is a multiple of 1k, the vector of k 1s. The importance of moderation in this context is...

Construing a collection of values of a sample statistic as a distribution is central to developing a coherent understanding of statistical inference. This paper discusses key developments that unfolded over three consecutive lessons in a classroom teaching experiment designed to support a group of high school students in developing such a construal. Instruction began by engaging students in act...

S tatistical analysis is an important tool in experimental research and is essential for the reliable interpretation of experimental results. It is essential that statistical design should be considered at the very beginning of a research project, not merely as an afterthought. For example if the sample size for an experiment only allows for an underpowered statistical analysis, then the interp...

Microarray technology has produced a huge body of time-course gene expression data and will continue to produce more. Such gene expression data has been proved useful in genomic disease diagnosis and drug design. The challenge is how to uncover useful information from such data by proper analysis methods such as significance analysis and clustering analysis. Many statistic-based significance an...

OBJECTIVE This paper describes a new class of space-time scan statistics designed for rapid detection of emerging disease clusters. We evaluate these methods on the task of prospective disease surveillance, and show that our methods consistently outperform the standard space-time scan statistic approach. BACKGROUND The space-time scan statistic [1] is a powerful statistical tool for prospective...

Medicaid spending growth has varied greatly over time. This article uses financial and statistical data to trace the history of Medicaid spending in relation to some of the major factors that have influenced its growth over the years. Periods of varying growth are divided into eight "eras," ranging from program startup in 1966 through the post-welfare reform period. Average expenditure and enro...

Items such as physical exam findings, radiographic interpretations, or other diagnostic tests often rely on some degree of subjective interpretation by observers. Studies that measure the agreement between two or more observers should include a statistic that takes into account the fact that observers will sometimes agree or disagree simply by chance. The kappa statistic (or kappa coefficient) ...