Monte Carlo transition probabilities

Transition probabilities governing the interaction of energy packets and matter are derived that allow Monte Carlo NLTE transfer codes to be constructed without simplifying the treatment of line formation. These probabilities are such that the Monte Carlo calculation asymptotically recovers the local emissivity of a gas in statistical equilibrium. Numerical experiments with one-point statistical equilibrium problems for Fe II and Hydrogen confirm this asymptotic behaviour. In addition, the resulting Monte Carlo emissivities are shown to be far less sensitive to errors in the populations of the emitting levels than are the values obtained with the basic emissivity formula.Comment: Improved text. Accepted for publication in A&

Aggregation of Affine Estimators

We consider the problem of aggregating a general collection of affine estimators for fixed design regression. Relevant examples include some commonly used statistical estimators such as least squares, ridge and robust least squares estimators. Dalalyan and Salmon (2012) have established that, for this problem, exponentially weighted (EW) model selection aggregation leads to sharp oracle inequalities in expectation, but similar bounds in deviation were not previously known. While results indicate that the same aggregation scheme may not satisfy sharp oracle inequalities with high probability, we prove that a weaker notion of oracle inequality for EW that holds with high probability. Moreover, using a generalization of the newly introduced $Q$-aggregation scheme we also prove sharp oracle inequalities that hold with high probability. Finally, we apply our results to universal aggregation and show that our proposed estimator leads simultaneously to all the best known bounds for aggregation, including $\ell_q$-aggregation, $q \in (0,1)$, with high probability

Orally-Dosed Citalopram Stimulates Small Intestinal Mucosal Growth

Parenterally-administered selective serotonin reuptake inhibitors (SSRI), such as citalopram, increase intestinal mucosal absorptive surface by day 7 of treatment. We hypothesized that enteral citalopram would also induce intestinal mucosal growth, thus allowing for therapy with an oral agent. In the study’s first phase, C57BL/6 mice received peanut butter (PB) pellets containing 10, 50, or 100 mg/kg/day citalopram for 7 days; or 25 mg/kg/day citalopram for 14 or 21 days; or plain PB pellets for 7, 14, or 21 days. In the second phase, C57BL/6 mice received 0, 10, 25, or 50 mg/kg/day citalopram in drinking water for 2, 3, 6, or 8 weeks, or for 6 weeks followed by 2 weeks of drug withdrawal. Two-centimeter ileal segments were harvested and prepared for microscopic assessment of villus height (VH), crypt depth (CD), villus width (VW), and crypt width (CW). Mucosal surface area (MSA) was calculated and data were compared using Student’s t-test. Enteral citalopram given for 14 days in PB pellets resulted in an increased VH (

The effect of forecast bias on market behavior: evidence from experimental asset markets

This paper reports the results of 15 experimental asset markets designed to investigate the effect of optimistic forecast bias on market behavior. Each market is organized as a double oral auction in which participants trade a single-period asset with uncertain value. Traders are informed of the asset value distribution and, prior to trading, given the opportunity to acquire a forecast of the asset's period-end value. The degree of forecast bias is manipulated across experimental sessions so that in some sessions the forecast contains a systematic, upward (low or high) bias. We conduct sessions with inexperienced and experienced traders. The results suggest that market prices are supportive of a full revelation unbiased price in the unbiased markets and the experienced, low-bias markets. The results from the low-bias markets indicate that as long as traders have sufficient experience with such forecasts, asset prices reflect the debiased forecasts. In contrast, we find no evidence that high-bias forecasts are reflected in market prices, regardless of experience. We also find that the demand for forecasted information persists over time, but it is greater in the unbiased and low-bias conditions than in the high-bias condition. Finally, we provide little evidence that the net profit (that is, net of the information cost) of informed and uninformed traders differs, regardless of bias condition or experience level.Forecasting ; Asset pricing

Asset prices and informed traders' abilities: evidence from experimental asset markets

This study reports the results of fifteen experimental asset markets designed to investigate the effects of forecasts on market prices, traders' abilities to assess asset value, and the link between the two. Across the fifteen markets, the authors investigate alternative forecast-generating processes. In some markets the process produces an unbiased estimate of asset value and in others a biased estimate. The processes generating the biased forecasts, though, are less variable than the process generating the unbiased forecast. The authors find that, in general, period-end asset price reflects private forecasts, regardless of the forecast-generating process. Subsequently, they investigate whether traders' abilities to use forecasts differ across the forecast-generating processes. The authors find that most are able to properly use unbiased forecasts. They refer to them as smart traders. By comparison, a significant proportion is unable to properly use biased forecasts (typically traders' adjustments for bias are insufficient). Linking market outcomes and traders' abilities, the authors find that asset price appears to properly reflect unbiased forecasts as long as the market includes at least two smart informed traders who have sufficient ability to influence market outcomes. To obtain a comparable result in markets with the biased forecast, at least three smart informed traders with sufficient ability to influence market outcomes are necessary.Forecasting ; Markets ; Financial markets ; Risk

Uncertain litigation cost and seller behavior: Evidence from an auditing game

This paper reports the results of two experiments, each consisting of six sessions, designed to investigate difficulties that arise in estimating expected litigation costs in an auditing game. In each experimental session, the game consists of a series of periods in which sellers submit sealed offers to computerized buyers and, if hired, choose an effort level (low or high). The effort level affects the certain (direct) and uncertain (litigation) costs of performing the engagement. Across the two experiments, we vary the uncertainty surrounding the determination of the expected litigation cost. Our results strongly suggest that cognitive limitations hinder sellers' abilities to estimate total expected litigation costs. Across both experiments we observe a nontrivial number of suboptimal effort choices. Moreover, as the uncertainty of determining the expected litigation cost increases, the frequency of observed fee offers below the total expected cost of an engagement increases markedly.Accounting