Learning Bayesian networks from data: An information-theory based approach

This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.

Water requirements as a bottleneck in the reintroduction of European roe deer to the southern edge of its range

Success rates of reintroduction programs are low, often owing to a lack of knowledge of site-specific ecological requirements. A reintroduction program of European roe deer (Capreolus capreolus (L., 1758)) in a dry Mediterranean region in Israel provides an opportunity to study the bottleneck effect of water requirements on a mesic-adapted species. Four does were hand-reared and released in a 10 ha site consisting of an early succession scrubland and a mature oak forest. We measured daily energy expenditure (DEE) and water turnover (WTO) using the doubly labeled water technique during summer and winter. DEE was similar in the summer and winter, but there was a significant difference in WTO and in the source of gained water. In winter, WTO was 3.3 L/day, of which 67% was obtained from vegetation. In summer, WTO dropped to 2.1 L/day, of which only 20% was obtained from the diet and 76% was gained from drinking. When the water source was moved to a nonpreferred habitat, drinking frequency dropped significantly, but water consumption remained constant. In a dry Mediterranean environment, availability of free water is both a physiological contraint and a behavioral constraint for roe deer. This study demonstrates the importance of physiological and behavioral feasibility studies for reintroduction programs.

Valuing the cultural monuments of Armenia: Bayesian updating of prior beliefs in contingent valuation

The most appropriate way to measure the social benefits of conserving built cultural heritage sites is to ask the beneficiaries of conservation interventions how much they would be willing to pay for them. We use contingent valuation - a survey-based approach that elicits willingness to pay (WTP) directly from individuals - to estimate the benefits of a nationwide conservation of built cultural heritage sites in Armenia. The survey was administered to Armenian nationals living in Armenia, and obtained extensive information about the respondents' perceptions of the current state of conservation of monuments in Armenia, described the current situation, presented a hypothetical conservation program, elicited WTP for it, and queried individuals about what they thought would happen to monument sites in the absence of the government conservation program. We posit that respondents combined the information about the fate of monuments provided by the questionnaire with their prior beliefs, and that WTP for the good, or program, is likely to be affected by these updated beliefs. We propose a Bayesian updating model of prior beliefs, and empirically implement it with the data from our survey. We found that uncertainty about what would happen to monuments in the absence of the program results in lower WTP amounts. © 2008 Pion Ltd and its Licensors.

Rarity, pseudodiagnosticity and Bayesian reasoning

Three experiments investigated the effect of rarity on people's selection and interpretation of data in a variant of the pseudodiagnosticity task. For familiar (Experiment 1) but not for arbitrary (Experiment 3) materials, participants were more likely to select evidence so as to complete a likelihood ratio when the initial evidence they received was a single likelihood concerning a rare feature. This rarity effect with familiar materials was replicated in Experiment 2 where it was shown that participants were relatively insensitive to explicit manipulations of the likely diagnosticity of rare evidence. In contrast to the effects for data selection, there was an effect of rarity on confidence ratings after receipt of a single likelihood for arbitrary but not for familiar materials. It is suggested that selecting diagnostic evidence necessitates explicit consideration of the alternative hypothesis and that consideration of the possible consequences of the evidence for the alternative weakens the rarity effect in confidence ratings. Paradoxically, although rarity effects in evidence selection and confidence ratings are in the spirit of Bayesian reasoning, the effect on confidence ratings appears to rely on participants thinking less about the alternative hypothesis.

High precision C-14 dating of Holocene peat deposits: A comparison of Bayesian calibration and wiggle-matching approaches

The chronologies of five northern European ombrotrophic peat bogs subjected to a large ANIS C-14 dating effort (32-44 dates/site) are presented here. The results of Bayesian calibration (BCal) of dates with a prior assumption of chronological ordering were compared with a Bayesian wiggle-match approach (Bpeat) which assumes constant linear accumulation over sections of the peat profile. Interpolation of BCal age estimates of dense sequences of C-14 dates showed variable patterns of peat accumulation with time, with changes in accumulation occurring at intervals ranging from 20 to 50 cm. Within these intervals, peat accumulation appeared to be relatively linear. Close analysis suggests that some of the inferred variations in accumulation rate were related to the plant macrofossil composition of the peat. The wiggle-matched age-depth models had relatively high chronological uncertainty within intervals of closely spaced 14 C dates, suggesting that the premise of constant linear accumulation over large sections of the peat profile is unrealistic. Age models based on the assumption of linear accumulation over large parts of a peat core (and therefore only effective over millennial timescales), are not compatible with studies examining environmental change during the Holocene, where variability often occurs at decadal to centennial time-scales. Ideally, future wiggle-match age models should be constrained, with boundaries between sections based on the plant macrofossil composition of the peat and physical-chemical parameters such as the degree of decomposition. Strategies for the selection of material for dating should be designed so that there should be enough C-14 dates to accurately reconstruct the peat accumulation rate of each homogeneous stratigraphic unit. (c) 2006 Elsevier Ltd. All rights reserved.