Extrapolation for Time-Series and Cross-Sectional Data

Extrapolation methods are reliable, objective, inexpensive, quick, and easily automated. As a result, they are widely used, especially for inventory and production forecasts, for operational planning for up to two years ahead, and for long-term forecasts in some situations, such as population forecasting. This paper provides principles for selecting and preparing data, making seasonal adjustments, extrapolating, assessing uncertainty, and identifying when to use extrapolation. The principles are based on received wisdom (i.e., experts’ commonly held opinions) and on empirical studies. Some of the more important principles are:• In selecting and preparing data, use all relevant data and adjust the data for important events that occurred in the past.• Make seasonal adjustments only when seasonal effects are expected and only if there is good evidence by which to measure them.• In extrapolating, use simple functional forms. Weight the most recent data heavily if there are small measurement errors, stable series, and short forecast horizons. Domain knowledge and forecasting expertise can help to select effective extrapolation procedures. When there is uncertainty, be conservative in forecasting trends. Update extrapolation models as new data are received.• To assess uncertainty, make empirical estimates to establish prediction intervals.• Use pure extrapolation when many forecasts are required, little is known about the situation, the situation is stable, and expert forecasts might be biased

Semi-sparse PCA

It is well-known that the classical exploratory factor analysis (EFA) of data with more observations than variables has several types of indeterminacy. We study the factor indeterminacy and show some new aspects of this problem by considering EFA as a specific data matrix decomposition. We adopt a new approach to the EFA estimation and achieve a new characterization of the factor indeterminacy problem. A new alternative model is proposed, which gives determinate factors and can be seen as a semi-sparse principal component analysis (PCA). An alternating algorithm is developed, where in each step a Procrustes problem is solved. It is demonstrated that the new model/algorithm can act as a specific sparse PCA and as a low-rank-plus-sparse matrix decomposition. Numerical examples with several large data sets illustrate the versatility of the new model, and the performance and behaviour of its algorithmic implementation

Life-course body size and perimenopausal mammographic parenchymal patterns in the MRC 1946 British birth cohort

Dense mammographic parenchymal patterns are associated with an increased risk of breast cancer. Certain features of body size have been found to be associated with breast cancer risk, but less is known about their relation to breast density. We investigated the association of birth size, childhood growth and life-course changes in body size with Wolfe grade in 1298 perimenopausal women from a British cohort of women born in 1946. The cohort benefits from repeated measures of body size in childhood and adulthood. We obtained mammograms for 90% of women who at age 53 years reported having previously had a mammogram. We found no associations with birth weight or maximum attained height. Body mass index (BMI) at age 53 years and breast size were independently and inversely associated with Wolfe grade (P-value for trend <0.001 for both). Women who reached puberty later were at a greater odds of a higher Wolfe grade than women who had an earlier puberty (odds ratio associated with a 1 year delay in menarche 1.14, 95% CI: 1.01-1.27, adjusted for BMI and breast size at mammography). A higher BMI at any age during childhood or adult life was associated with a reduction in the odds of a higher Wolfe grade, after controlling for breast size and BMI at mammography, for example, standardised odds ratio for height at age 7 was 0.72 (95% CI: 0.64, 0.81). These findings reveal the importance of taking life-course changes in body size, and not just contemporaneous measures, into account when using mammographic density as an intermediate marker for risk of breast cancer

Quantifying the effect of population mixing on childhood leukaemia risk: the Seascale cluster

A statistical model was developed based on Poisson regression of incidence of childhood leukaemia and non-Hodgkin’s lymphoma (NHL) in relation to population mixing among all 119 539 children born 1969–1989 to mothers living in Cumbria, north-west England, (excluding Seascale). This model was used to predict the number of cases in Seascale (the village adjacent to the Sellafield nuclear installation) children, born 1950–1989 and diagnosed before 1993. After allowing for age, the incidence of acute lymphoblastic leukaemia (ALL) and NHL was significantly higher among children born in areas with the highest levels of population mixing, relative risk (RR) = 11.7 (95% confidence interval (CI) 3.2–43) and was highest among children of incomers. The model predicted up to 3.0 (95% CI 1.3–6.0) cases of ALL/NHL in children born in Seascale compared to six observed and 2.0 (95% CI 1.0–3.4) cases in children resident, but not born, in Seascale compared to two observed. Population mixing is a significant risk factor for ALL/NHL, especially in young children, accounting for over 50% of cases in Cumbria and most cases in Seascale. © 1999 Cancer Research Campaig

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

A typology of practice narratives during the implementation of a preventive, community intervention trial

<p>Abstract</p> <p>Background</p> <p>Traditional methods of process evaluation encompass what components were delivered, but rarely uncover how practitioners position themselves and act relative to an intervention being tested. This could be crucial for expanding our understanding of implementation and its contribution to intervention effectiveness.</p> <p>Methods</p> <p>We undertook a narrative analysis of in-depth, unstructured field diaries kept by nine community development practitioners for two years. The practitioners were responsible for implementing a multi-component, preventive, community-level intervention for mothers of new babies in eight communities, as part of a cluster randomised community intervention trial. We constructed a narrative typology of approaches to practice, drawing on the phenomenology of Alfred Schutz and Max Weber's Ideal Type theory.</p> <p>Results</p> <p>Five types of practice emerged, from a highly 'technology-based' type that was faithful to intervention specifications, through to a 'romantic' type that held relationships to be central to daily operations, with intact relationships being the final arbiter of intervention success. The five types also differed in terms of how others involved in the intervention were characterized, the narrative form (<it>e.g</it>., tragedy, satire) and where and how transformative change in communities was best created. This meant that different types traded-off or managed the priorities of the intervention differently, according to the deeply held values of their type.</p> <p>Conclusions</p> <p>The data set constructed for this analysis is unique. It revealed that practitioners not only exercise their agency within interventions, they do so systematically, that is, according to a pattern. The typology is the first of its kind and, if verified through replication, may have value for anticipating intervention dynamics and explaining implementation variation in community interventions.</p

The patriotism of gentlemen with red hair: European Jews and the liberal state, 1789–1939

European Jewish history from 1789–1939 supports the view that construction of national identities even in secular liberal states was determined not only by modern considerations alone but also by ancient patterns of thought, behaviour and prejudice. Emancipation stimulated unprecedented patriotism, especially in wartime, as Jews strove to prove loyalty to their countries of citizenship. During World War I, even Zionists split along national lines, as did families and friends. Jewish patriotism was interchangeable with nationalism inasmuch as Jews identified themselves with national cultures. Although emancipation implied acceptance and an end to anti-Jewish prejudice in the modern liberal state, the kaleidoscopic variety of Jewish patriotism throughout Europe inadvertently undermined the idea of national identity and often provoked anti-Semitism. Even as loyal citizens of separate states, the Jews, however scattered, disunited and diverse, were made to feel, often unwillingly, that they were one people in exile

Negative Priming Under Rapid Serial Visual Presentation

Negative priming (NP) was examined under a new paradigm wherein a target and distractors were temporally separated using rapid serial visual presentation (RSVP). The results from the two experiments revealed that (a) NP was robust under RSVP, such that the responses to a target were slower when the target served as a distractor in a previous trial than when it did not; (b) NP was found regardless of whether the distractors appeared before or after the targets; and (c) NP was stronger when the distractor was more distinctive. These findings are generally similar to those on NP in the spatial search task. The implications for the processes causing NP under RSVP are discussed in the current paper