Disturbed galaxy clusters are more abundant in an X-ray volume-limited sample

We present first strong observational evidence that the X-ray cool-core bias or the apparent bias in the abundance of relaxed clusters is absent in our REFLEX volume-limited sample (ReVols). We show that these previously observed biases are due to the survey selection method such as for an flux-limited survey, and are not due to the inherent nature of X-ray selection. We also find that the X-ray luminosity distributions of clusters for the relaxed and for the disturbed clusters are distinct and a displacement of approximately 60 per cent is required to match two distributions. Our results suggest that to achieve more precise scaling relation one may need to take the morphology of clusters and their fractional abundance into account.Comment: A&A, 606, L4, 4 pages, 3 figure

Effective forecasting for supply-chain planning: an empirical evaluation and strategies for improvement

Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a simple univariate statistical method to produce a forecast and the subsequent judgmental adjustment of this by the company's demand planners to take into account market intelligence relating to any exceptional circumstances expected over the planning horizon. Based on four company case studies, which included collecting more than 12,000 forecasts and outcomes, this paper examines: i) the extent to which the judgmental adjustments led to improvements in accuracy, ii) the extent to which the adjustments were biased and inefficient, iii) the circumstances where adjustments were detrimental or beneficial, and iv) methods that could lead to greater levels of accuracy. It was found that the judgmentally adjusted forecasts were both biased and inefficient. In particular, market intelligence that was expected to have a positive impact on demand was used far less effectively than intelligence suggesting a negative impact. The paper goes on to propose a set of improvements that could be applied to the forecasting processes in the companies and to the forecasting software that is used in these processes

Confidence intervals of prediction accuracy measures for multivariable prediction models based on the bootstrap-based optimism correction methods

In assessing prediction accuracy of multivariable prediction models, optimism corrections are essential for preventing biased results. However, in most published papers of clinical prediction models, the point estimates of the prediction accuracy measures are corrected by adequate bootstrap-based correction methods, but their confidence intervals are not corrected, e.g., the DeLong's confidence interval is usually used for assessing the C-statistic. These naive methods do not adjust for the optimism bias and do not account for statistical variability in the estimation of parameters in the prediction models. Therefore, their coverage probabilities of the true value of the prediction accuracy measure can be seriously below the nominal level (e.g., 95%). In this article, we provide two generic bootstrap methods, namely (1) location-shifted bootstrap confidence intervals and (2) two-stage bootstrap confidence intervals, that can be generally applied to the bootstrap-based optimism correction methods, i.e., the Harrell's bias correction, 0.632, and 0.632+ methods. In addition, they can be widely applied to various methods for prediction model development involving modern shrinkage methods such as the ridge and lasso regressions. Through numerical evaluations by simulations, the proposed confidence intervals showed favourable coverage performances. Besides, the current standard practices based on the optimism-uncorrected methods showed serious undercoverage properties. To avoid erroneous results, the optimism-uncorrected confidence intervals should not be used in practice, and the adjusted methods are recommended instead. We also developed the R package predboot for implementing these methods (https://github.com/nomahi/predboot). The effectiveness of the proposed methods are illustrated via applications to the GUSTO-I clinical trial

Cosmicflows-2: I-band Luminosity - HI Linewidth Calibration

In order to measure distances with minimal systematics using the correlation between galaxy luminosities and rotation rates it is necessary to adhere to a strict and tested recipe. We now derive a measure of rotation from a new characterization of the width of a neutral Hydrogen line profile. Additionally, new photometry and zero point calibration data are available. Particularly the introduction of a new linewidth parameter necessitates the reconstruction and absolute calibration of the luminosity-linewidth template. The slope of the new template is set by 267 galaxies in 13 clusters. The zero point is set by 36 galaxies with Cepheid or Tip of the Red Giant Branch distances. Tentatively, we determine H0 = 75 km s-1 Mpc-1. Distances determined using the luminosity-linewidth calibration will contribute to the distance compendium Cosmicflows-2.Comment: Accepted for publication in The Astrophysical Journal, 27 pages, 18 figure

Early vocabulary development in deaf native signers: a British Sign Language adaptation of the communicative development inventories

Background: There is a dearth of assessments of sign language development in young deaf children. This study gathered age-related scores from a sample of deaf native signing children using an adapted version of the MacArthur-Bates CDI (Fenson et al., 1994). Method: Parental reports on children’s receptive and expressive signing were collected longitudinally on 29 deaf native British Sign Language (BSL) users, aged 8–36 months, yielding 146 datasets. Results: A smooth upward growth curve was obtained for early vocabulary development and percentile scores were derived. In the main, receptive scores were in advance of expressive scores. No gender bias was observed. Correlational analysis identified factors associated with vocabulary development, including parental education and mothers’ training in BSL. Individual children’s profiles showed a range of development and some evidence of a growth spurt. Clinical and research issues relating to the measure are discussed. Conclusions: The study has developed a valid, reliable measure of vocabulary development in BSL. Further research is needed to investigate the relationship between vocabulary acquisition in native and non-native signers

A meta-analysis of wage-risk estimates of the value of a statistical life

This paper presents the results of a meta-analysis of estimates of the value of statistical life (VOSL). Data on the sample characteristics, data sources and analytical approach used to derive some 60 separate estimates in 17 published papers are used in the analysis. Tests lead us to reject the hypothesis that this sample shows evidence of publication bias. A meta-regression of these estimates provides evidence that VOSL is increasing in income but is invariant with respect to baseline risk. Controlling for aspects of the sample, data sources and analytical approach allows us to derive a best estimate of the VOSL of around $7 million

The Magnitude of Random Appraisal Error in Commercial Real Estate Valuation

Analysis of more than seven hundred pairs of simultaneous independent appraisals of institutional-grade commercial properties shows that the standard deviation of the random component of appraisal error is approximately 2%. Random appraisal error appears constant across both time and the institutional-grade investment universe, except during infrequent periods of real estate market gridlock. Most appraisal error is deterministic in nature, even though it usually appears random in routine cross-sectional analysis. Such appraisal error can be constrained and reduced by investment management control systems.