This paper estimates an additive model semiparametrically, while automatically selecting the significant independent variables and the app~opriatc power transformation of the dependent variable. The nonlinear variables arc modeled as regression splincs, with significant knots selected fiom a large number of candidate knots. The estimation is made robust by modeling the errors as a mixture of no...

This paper examines the performance gains achievable by adding interblock memory to, and altering the mapping of coded bits to symbols in, block coded modulation systems. The channel noise considered is additive Gaussian, and the twin design goals are to maximize the asymptotic coding gain and to minimize the number of apparent nearest neighbors. In the case of the additive white Gaussian noise...

A (β, )-hopset is, informally, a weighted edge set that, when added to a graph, allows one to get from point a to point b using a path with at most β edges (“hops”) and length (1 + ) dist(a, b). In this paper we observe that Thorup and Zwick’s sublinear additive emulators are also actually (O(k/ ), )hopsets for every > 0, and that with a small change to the Thorup-Zwick construction, the size o...

We investigate the group processes involved in effort estimation in the context of Project Management. The groups considered are formed by “experts” (people with specific technical competence) and “non-experts” (people with less specific technical competence, usually experts in related fields), because the typically complementary bias of the two classes contribute to a more balanced estimate. I...

This paper contributes to the axiomatization of additive rules for ranking sets of objects under the psychological principle of categorization. Firstly we proceed with the case where the elements in the sets are categorized into at most three groups, namely good (with value 1), neutral (with value 0), and bad (with value−1). Secondly, we solve the case where there are only good and neutral elem...

In this paper a novel distributed algorithm for blind macro-calibration in sensor networks based on consensus is proposed. The algorithm is formulated as a set of gradient-type recursions for estimating parameters of sensor calibration functions, starting from local criteria defined as weighted sums of mean square differences between the outputs of neighboring sensors. It is proved that the alg...

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is...

Research on food decision making is often based on the assumption that people take many different aspects into account and weight and add them according to their personally assessed importance. Yet there is a growing body of research suggesting that people's decisions can often be better described by simple heuristics-rules of thumb that people use to make choices based on only a few important ...

The speech intelligibility index (SII) (ANSI S3.5-1997) provides a means for estimating speech intelligibility under conditions of additive stationary noise or bandwidth reduction. The SII concept for estimating intelligibility is extended in this paper to include broadband peak-clipping and center-clipping distortion, with the coherence between the input and output signals used to estimate the...

We analyze temporal approximation schemes based on overlapping domain decompositions. As such schemes enable computations on parallel and distributed hardware, they are commonly used when integrating large-scale parabolic systems. Our analysis is conducted by first casting the domain decomposition procedure into a variational framework based on weighted Sobolev spaces. The time integration of a...