The Effects of feedback on judgmental interval predictions

Cataloged from PDF version of article.The majority of studies of probability judgment have found that judgments tend to be overconfident and that the degree of overconfidence is greater the more difficult the task. Further, these effects have been resistant to attempts to ‘debias’ via feedback. We propose that under favourable conditions, provision of appropriate feedback should lead to significant improvements in calibration, and the current study aims to demonstrate this effect. To this end, participants first specified ranges within which the true values of time series would fall with a given probability. After receiving feedback, forecasters constructed intervals for new series, changing their probability values if desired. The series varied systematically in terms of their characteristics including amount of noise, presentation scale, and existence of trend. Results show that forecasts were initially overconfident but improved significantly after feedback. Further, this improvement was not simply due to ‘hedging’, i.e. shifting to very high probability estimates and extremely wide intervals; rather, it seems that calibration improvement was chiefly obtained by forecasters learning to evaluate the extent of the noise in the series. D 2003 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved

XML Reconstruction View Selection in XML Databases: Complexity Analysis and Approximation Scheme

Query evaluation in an XML database requires reconstructing XML subtrees rooted at nodes found by an XML query. Since XML subtree reconstruction can be expensive, one approach to improve query response time is to use reconstruction views - materialized XML subtrees of an XML document, whose nodes are frequently accessed by XML queries. For this approach to be efficient, the principal requirement is a framework for view selection. In this work, we are the first to formalize and study the problem of XML reconstruction view selection. The input is a tree $T$, in which every node $i$ has a size $c_i$ and profit $p_i$, and the size limitation $C$. The target is to find a subset of subtrees rooted at nodes $i_1,\cdots, i_k$ respectively such that $c_{i_1}+\cdots +c_{i_k}\le C$, and $p_{i_1}+\cdots +p_{i_k}$ is maximal. Furthermore, there is no overlap between any two subtrees selected in the solution. We prove that this problem is NP-hard and present a fully polynomial-time approximation scheme (FPTAS) as a solution

Currency forecasting: an investigation of extrapolative judgement

Cataloged from PDF version of article.This paper aims to explore the potential effects of trend type, noise and forecast horizon on experts' and novices' probabilistic forecasts. The subjects made forecasts over six time horizons from simulated monthly currency series based on a random walk, with zero, constant and stochastic drift, at two noise levels. The difference between the Mean Absolute Probability Score of each participant and an AR(1) model was used to evaluate performance. The results showed that the experts performed better than the novices, although worse than the model except in the case of zero drift series. No clear expertise effects occurred over horizons, albeit subjects' performance relative to the model improved as the horizon increased. Possible explanations are offered and some suggestions for future research are outlined

On the Delay Margin for Consensus in Directed Networks of Anticipatory Agents

We consider a linear consensus problem involving a time delay that arises from predicting the future states of agents based on their past history. In case the agents are coupled in a connected and undirected network, the exact condition for consensus is that the delay be less than a constant threshold that is independent of the network topology or size. In directed networks, however, the situation is quite different. We show that the allowable maximum delay for consensus depends on the network topology in a nontrivial way. We study this delay margin in several network constellations, including various circulant networks with directed links. We show that the delay margin depends not only on the number of neighbors, but also on the directionality of connections with those neighbors. Furthermore, the delay margin improves as the circulant networks are rewired en route to a small-world configuration. © 201

A delayed consensus algorithm in networks of anticipatory agents

We introduce and analyze a delayed consensus algorithm as a model for interacting agents using anticipation of their neighbors' states to improve convergence to consensus. We derive a necessary and sufficient condition for the system to reach consensus. Furthermore, we explicitly calculate the dominant characteristic root of the consensus problem as a measure of the speed of convergence. The results show that the anticipatory algorithm can improve the speed of consensus, especially in networks with poor connectivity. Hence, anticipation can improve performance in networks if the delay parameter is chosen judiciously, otherwise the system might diverge as agents try to anticipate too aggressively into the future. © 2016 EUCA

Non-equilibrium dynamics of stochastic point processes with refractoriness

Stochastic point processes with refractoriness appear frequently in the quantitative analysis of physical and biological systems, such as the generation of action potentials by nerve cells, the release and reuptake of vesicles at a synapse, and the counting of particles by detector devices. Here we present an extension of renewal theory to describe ensembles of point processes with time varying input. This is made possible by a representation in terms of occupation numbers of two states: Active and refractory. The dynamics of these occupation numbers follows a distributed delay differential equation. In particular, our theory enables us to uncover the effect of refractoriness on the time-dependent rate of an ensemble of encoding point processes in response to modulation of the input. We present exact solutions that demonstrate generic features, such as stochastic transients and oscillations in the step response as well as resonances, phase jumps and frequency doubling in the transfer of periodic signals. We show that a large class of renewal processes can indeed be regarded as special cases of the model we analyze. Hence our approach represents a widely applicable framework to define and analyze non-stationary renewal processes.Comment: 8 pages, 4 figure

Evaluating predictive performance of judgemental extrapolations from simulated currency series

Cataloged from PDF version of article.Judgemental forecasting of exchange rates is critical for ®nancial decision-making. Detailed investigations of the potential e ects of time-series characteristics on judgemental currency forecasts demand the use of simulated series where the form of the signal and probability distribution of noise are known. The accuracy measures Mean Absolute Error (MAE) and Mean Squared Error (MSE) are frequently applied quantities in assessing judgemental predictive performance on actual exchange rate data. This paper illustrates that, in applying these measures to simulated series with Normally distributed noise, it may be desirable to use their expected values after standardising the noise variance. A method of calculating the expected values for the MAE and MSE is set out, and an application to ®nancial experts' judgemental currency forecasts is presented. Ó 1999 Elsevier Science B.V. All rights reserved

The cultural impact of hidden curriculum on language learners: A review and some implications for curriculum design

With reference to theory and research, this chapter discusses the hidden curriculum of language textbooks and other teaching materials where culture, gender, race, or other topics associated with equality, diversity, and representativeness were presented in biased ways. Hidden curriculum may describe, present, or elicit stereotypes and reproduce cultural, gender, and racial bias in subtle ways; sometimes even teachers may not notice what the curriculum refers to or they may perceive stereotyping as harmless. This makes sociolinguistic problems with regard to use of a purist and monolithic cultural content more salient than ever. Yet, the new sociolinguistic landscape of language teaching where changing needs of language learners might not be accurately represented in teaching materials require the revision of current curricula and pedagogical practices. Therefore, this chapter draws conclusions from empirical studies on the topic and provides some implications for teaching and materials design

Mapping dynamical systems onto complex networks

A procedure to characterize chaotic dynamical systems with concepts of complex networks is pursued, in which a dynamical system is mapped onto a network. The nodes represent the regions of space visited by the system, while edges represent the transitions between these regions. Parameters used to quantify the properties of complex networks, including those related to higher order neighborhoods, are used in the analysis. The methodology is tested for the logistic map, focusing the onset of chaos and chaotic regimes. It is found that the corresponding networks show distinct features, which are associated to the particular type of dynamics that have generated them.Comment: 13 pages, 8 eps files in 5 figure