I discuss a novel technique for periodically extending by reflection an ordered series of phase-difference {xk.} to yield estimation of new frequency and time variances having improved longterm confidence and the same mean as the Allan variance. In addition, I describe a correction to a negative bias in the sample variance based on the actual number of observations in the measurements at long t...

Between-day variance is an ambiguous term representing either total variance or pure between-day variance. In either case, it is often incorrectly calculated even though analysis of variance (ANOVA) and other excellent methods of estimation are available. We used statistical theory to predict the magnitude of error expected from using several intuitive approaches to estimation of variance compo...

Brain activation studies based on PET or fMRI seek to explore neuroscience questions by statistically analyzing the acquired images to produce statistical parametric images (SPIs). An increasingly wide range of univariate and multivariate analysis techniques are used to generate SPIs in order to detect mean-signal activations and/or long-range spatial interactions. However, little is known abou...

We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBayes classifiers delivering the same probability estimates as would be obtained if the correct probability density functions were employed. We discuss the factors that might affect naive-Bayes classification error under ...

This paper investigates the effect of interactions between the Walsh codes and data sequences on the statistical moments of the forward-link CDMA signal. Of primary interest is the normalized fourth-order moment, which is referred to as the “power variance”. Several techniques for reducing the power variance of the CDMA signal are discussed that are based on Walsh code selection and data encodi...

This paper is concerned with methods for analyzing quantitative, noncategorical profile data, e.g., a battery of tests given to individuals in one or more groups. It is assumed that the variables have a multinormal distribution with an arbitrary variance-covariance matrix. Approximate procedures based on classical analysis of variance are presented, including an adjustment to the degrees of fre...

Outliers, level shifts, and variance changes are commonplace in applied time series analysis. However, their existence is often ignored and their impact is overlooked, for the lack of simple and useful methods to detect and handle those extraordinary events. The problem of detecting outliers, level shifts, and variance changes in a univariate time series is considered. The methods employed are ...