53 resultados para Combination of short term inflation forecast models

em CentAUR: Central Archive University of Reading - UK


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In this field experiment, sewage sludge was applied at 0, 5, 10, and 50 t ha(-1), and the availability of Cd, Ni, Pb, and Zn was assessed both by ryegrass uptake and by DTPA extractions. The aim was to investigate the role of important soil parameters, particularly pH, on heavy metal availability. It was found that metal uptake and extractability increased significantly in the 50 t ha(-1) treatment. In the 16th week of the experiment there was a significant, although temporary, increase in DTPA-extractable Cd, Ni, and Zn concentrations. Metal concentrations in ryegrass were also significantly elevated in week 20 compared to the subsequent cuttings. These fluctuations in both DTPA and ryegrass uptake occurred only at 50 t ha(-1) and were probably induced by a sudden pH decrease measured in the same treatment in week 16. This suggests that soils which have received high applications of sewage sludge may be prone to fluctuations in metal availability. (c) 2007 Elsevier Ltd. All rights reserved.

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The fair weather atmospheric electrical current (Jz) couples the ionosphere to the lower atmosphere and thus provides a route by which changes in solar activity can modify processes in the lower troposphere. This paper examines the temporal variations and spectral characteristics of continuous measurements of Jz conducted at the Wise Observatory in Mitzpe-Ramon, Israel (30°35′ N, 34°45′ E), during two large CMEs, and during periods of increased solar wind density. Evidence is presented for the effects of geomagnetic storms and sub-storms on low latitude Jz during two coronal mass ejections (CMEs), on 24–25th October 2011 and 7–8th March 2012, when the variability in Jz increased by an order of magnitude compared to normal fair weather conditions. The dynamic spectrum of the increased Jz fluctuations exhibit peaks in the Pc5 frequency range. Similar low frequency characteristics occur during periods of enhanced solar wind proton density. During the October 2011 event, the periods of increased fluctuations in Jz lasted for 7 h and coincided with fluctuations of the inter-planetary magnetic field (IMF) detected by the ACE satellite. We suggest downward mapping of ionospheric electric fields as a possible mechanism for the increased fluctuations.

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This article is a direct response to a recent observation in the literature that managers appear to be short-term oriented in their assessment of the performance of an export venture (Madsen 1998). On the basis of a cross-national survey of exporting firms, the authors present a three-dimensional scale for assessing managerial judgment of short-term export performance (i.e., the STEP scale). The three dimensions are (1) satisfaction with short-term performance improvement, (2) short-term exporting intensity improvement, and (3) expected short-term performance improvement. The scale presents evidence of reliability as well as convergent, discriminant, and nomological validity, and it reveals factorial similarity and factorial equivalence across both samples. The authors outline managerial and public policy implications that stem from the scale and identify avenues for further export marketing research.

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In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short- and long-term endpoints.

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The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

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Seamless phase II/III clinical trials in which an experimental treatment is selected at an interim analysis have been the focus of much recent research interest. Many of the methods proposed are based on the group sequential approach. This paper considers designs of this type in which the treatment selection can be based on short-term endpoint information for more patients than have primary endpoint data available. We show that in such a case, the familywise type I error rate may be inflated if previously proposed group sequential methods are used and the treatment selection rule is not specified in advance. A method is proposed to avoid this inflation by considering the treatment selection that maximises the conditional error given the data available at the interim analysis. A simulation study is reported that illustrates the type I error rate inflation and compares the power of the new approach with two other methods: a combination testing approach and a group sequential method that does not use the short-term endpoint data, both of which also strongly control the type I error rate. The new method is also illustrated through application to a study in Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

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We test the expectations theory of the term structure of U.S. interest rates in nonlinear systems. These models allow the response of the change in short rates to past values of the spread to depend upon the level of the spread. The nonlinear system is tested against a linear system, and the results of testing the expectations theory in both models are contrasted. We find that the results of tests of the implications of the expectations theory depend on the size and sign of the spread. The long maturity spread predicts future changes of the short rate only when it is high.

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In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

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A manipulated increase in acid deposition (15 kg S ha(-1)), carried out for three months in a mature Scots pine (Pinus sylvestris) stand on a podzol, acidified the soil and raised dissolved Al at concentrations above the critical level of 5 mg l(-1) previously determined in a controlled experiment with Scots pine seedlings. The induced soil acidification reduced tree fine root density and biomass significantly in the top 15 cm of soil in the field. The results suggested that the reduction in fine root growth was a response not simply to high Al in solution but to the depletion of exchangeable Ca and Mg in the organic layer, K deficiency, the increase in NH4:NO3 ratio in solution and the high proton input to the soil by the acid manipulation. The results from this study could not justify the hypothesis of Al-induced root damage under field conditions, at least not in the short term. However, the study suggests that a short exposure to soil acidity may affect the fine root growth of mature Scots pine.

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Study objectives: There is a possibility that lower air, moisture and light protection could impact on physico-chemical stability of medicines inside multi-compartment compliance aids (MCCAs), although this has not yet been proved. The objectives of the study were to examine the physico-chemical stability of atenolol tablets stored in a compliance aid at room temperature, and at elevated temperature and humidity to simulate practice conditions. Methods: Atenolol 100 mg tablets in 28-chamber, plastic compliance aids with transparent lids were stored for four weeks at room temperature and at 40°C with 75% relative humidity. Tablets were also stored at room temperature in original packaging and Petri dishes. Physical tests were conducted to standards as laid down in the British Pharmacopoeia 2005, and dissolution to those of the United States Pharmacopoeia volume 24. Chemical stability was assessed by a validated high-performance liquid chromatography (HPLC) method. Results: Tablets at room temperature in original packaging, in compliance aids and Petri dishes remained the same in appearance and passed physico-chemical tests. Tablets exposed to 40°C with 75% relative humidity in compliance aids passed tests for uniformity of weight, friability and chemical stability but became pale and moist, softer (82 newtons ± 4; p< 0.0001) than tablets in the original packaging (118 newtons ± 6), more friable (0.14% loss of mass) compared with other tablets (0.005%), and failed the tests for disintegration (>15 minutes) and dissolution (only 15% atenolol released at 30 minutes). Conclusion: Although chemical stability was unaffected, storage in compliance aids at 40°C with 75% relative humidity softened atenolol tablets, prolonged disintegration time and hindered dissolution which could significantly reduce bioavailability. This formulation could be suitable for storage in compliance aids at 25°C, but not in hotter, humid weather.

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The hypothesis that dairy cows partially suckling their calves would ovulate following removal of calves when restored to positive energy balance by a short-term increase in supplementation was investigated in 65 crossbred cows. Five treatments (T1, T2, T3, T4, and T5) that differed in the amount of total concentrate fed from calving to week 24 were involved. Calves were allowed to suck residual milk to 12 weeks of age. Energy balance was estimated by measuring intake, milk yield and organic matter digestibility. The occurrence of ovulation was determined by the analysis of milk progesterone (P4) concentration. Four groups that were receiving additional supplementation were restored to positive energy balance, while the control group (T I) remained in negative energy balance. The percentage of cows ovulating was 36%, 58%, 92%, 90% and 60% for T1, T2, T3, T4 and T5, respectively (P = 0.026). Comparison of the timing of ovulation for combined results from T1+T2 and T3+T4+T5 estimated mean time to fail to ovulate as 110 +/- 9.0 and 87 +/- 7.6 days, respectively (p = 0.023). The percentage of the cows showing oestrus was 9%, 8%, 33%, 40% and 40% for T1, T2, T3, T4 and T5, respectively (P = 0.197). Short-term increases in supplementation are unlikely to be an attractive means of reducing calving intervals.