We describe the construction of statistical models that provide inferences about the probability that subjects will consider events to be memory landmarks. We review methods and report results of experiments probing the classification accuracy and receiver-operator characteristics of the models. Then, we discuss opportunities for integrating models of memory landmarks into computing application...

We can adapt existing techniques for the statistical modeling of music to the modeling of the quality of musical performance, resulting in a fine-grained statistical understanding of ’hardness’ in music performance. This drives AI-assisted applications for improving skill. We present modeling results using various probabilistic models to model performance in the simplified setting of rhythm games.

Smooth curves a.re often used to illustrate the relationship between two variables. They are also an important building block in many recent statistical models. A procedure to estimate such a curve is called a smoother. This paper discusses currently available smoothers and introduces the class of maximum likelihood smoothers. A variety of other statistical techniques are shown to be applicable...

This article presents a conceptual framework for clarifying the network hypotheses embedded in policy theories and how they relate to macrolevel political institutions and microlevel political behavior. We then describe the role of statistical models of networks for testing these hypotheses, including the problem of operationalizing theoretical concepts with the parameters of statistical models...

For second-hand products sold with warranty, the expected warranty cost for an item to the manufacturer, depends on (i) the age and/or usage as well as the maintenance history for the item and (ii) the terms of the warranty policy. The paper develops probabilistic models to compute the expected warranty cost to the manufacturer when the items are sold with free replacement or pro rata warrantie...

Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across leve...

Recent research on contingency judgment indicates that the judged predictiveness of a cue is dependent on the predictive strengths of other cues. Two classes of models correctly predict such cue interaction: associative models and statistical models. However, these models differ in their predictions about the effect of trial order on cue interaction. In five experiments reported here, college s...

Although abiotic factors, together with dispersal and biotic interactions, are often suggested to explain the distribution of species and their abundances, species distribution models usually focus on abiotic factors only. We propose an integrative framework linking ecological theory, empirical data and statistical models to understand the distribution of species and their abundances together w...

This study extensively compares two statistical models for the analysis of binary data from longitudinal studies. The first model was proposed by Zeger, Liang, and Self, which was abbreviated as ZLS model and another model was proposed by Origasa. The comparison focuses on both analytical and statistical view-points. The first discusses a type of the models and the second evaluates the effect f...

Are there absolute limits to the speed at which animals can run? If so, how close are present-day individuals to these limits? I approach these questions by using three statistical models and data from competitive races to estimate maximum running speeds for greyhounds, thoroughbred horses and elite human athletes. In each case, an absolute speed limit is definable, and the current record appro...