Data Aggregation and Information Loss

Analysts often use a single average or otherwise aggregated price series to represent several geographic or product markets even when disaggregate data are available. We hypothesize that such an approach may not be appropriate under some circumstances, such as when only long-term relationships hold among price series or when homogeneous but relatively perishable products are considered. This question is of particular relevance in agriculture because of seasonality in production and harvest across various production regions, and the effect of changes in demand as substitute crops become available. We analyze this question in the context of fresh strawberry production. We find that in the case of the strawberry market, aggregate series are appropriate for long-term decision analysis, but some information loss occurs when conducting short-term decision analysis.strawberry, price, cointegration, Granger causality, average price, Research Methods/ Statistical Methods,

Analysis and modelling of the COLOSS international data set 2010-2011

Colony Losses have been calculated for Netherlands, Germany, Poland, Hungary, Austria, Denmark, Ireland and the UK. The following approach was used. Initial analysis was conducted using examination of the data and descriptive statistics. Some inconsistencies in the data were found, for further consideration. Using appropriate selection of cases, colony losses were calculated for the countries above individually and also overall, using overall proportion of loss, CDS type loss and loss due to queen problems, and also the mean/median of the individual loss rates per beekeeper. The proportions of beekeepers suffering any loss of any kind were also calculated. We both included and excluded Scotland as part of the UK. Differences between countries were found based on 95% confidence intervals for proportion of losses. Some suggestions are made in relation to data quality control and data modelling. Logistic regression/binomial-logit generalised linear modelling may be used to model the chance of any loss, any CDS loss, or loss due to queen problems

Universal scaling dependence of QCD energy loss from data driven studies

In this paper we study the energy loss of jets in the QGP via the nuclear modification factor $R_{\textrm{AA}}$ for unidentified particles at high $p_{\textrm{T}}$ ($\gtrsim 10 \textrm{GeV}/c$) in and out of the reaction plane of the collision. We argue that at such a high $p_{\textrm{T}}$ there are no genuine flow effects and, assuming that the energy loss is only sensitive to initial characteristics such as the density and geometry, find that $R_{\textrm{AA}}$ depends linearly on the (RMS) length extracted from Glauber simulations. Furthermore we observe that for different centrality classes the density dependence of the energy loss enters as the square root of the charged particle multiplicity normalized to the initial overlap area. The energy loss extracted for RHIC and LHC data from the $R_{\textrm{AA}}$ is found to exhibit a universal behavior.Comment: 15 pages, 5 figures, version to be published in Phys. Rev.