985 resultados para error rates


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This paper investigates the impact of policies to promote the adoption of LEED-certified buildings across CBSA in the United States. Drawing upon a unique database that combines data from a large number of sources and using a number of regression procedures, the determinants of the proportion LEED-certified space for more than 170 CBSA in the US is modeled. LEED-certified space still accounts for a relatively small proportion of commercial stock in all markets. The average proportion is less than 1%. There is no conclusive evidence of a positive impact of policy intervention on the levels of LEED-certified space. However, after accounting for bias introduced by non-random assignment of policies, we find preliminary evidence of a positive impact of city-level green building incentives. There is a significant positive association between market size and indicators of economic vitality on proportions of LEED-certified space.

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Earthworms secrete granules of calcium carbonate. These are potentially important in soil biogeochemical cycles and are routinely recorded in archaeological studies of Quaternary soils. Production rates of calcium carbonate granules by the earthworm Lumbricus terrestris L. were determined over 27 days in a range of soils with differing chemical properties (pH, organic matter content, water holding capacity, bulk composition, cation exchange capacity and exchangeable cations). Production rate varied between soils, lay in the range 0–0.043 mmolCaCO3 (0–4.3 mg) earthworm−1 d−1 with an average rate of 8 × 10−3 mmolCaCO3 (0.8 mg) earthworm−1 d−1 and was significantly correlated (r = 0.68, P ≤ 0.01) with soil pH. In a second experiment lasting 315 days earthworms repeatedly (over periods of 39–57 days) produced comparable masses of granules. Converting individual earthworm granule production rates into fluxes expressed on per hectare of land per year basis depends heavily on estimates of earthworm numbers. Using values of 10–20 L. terrestris m−2 suggests a rate of 18– 3139 molCaCO3 ha−1 yr−1. Data obtained from flow-through dissolution experiments suggest that at near neutral pH, granule geometric surface areanormalised dissolution rates are similar to those for other biogenic and inorganic calcium carbonate. Fits of the data to the dissolution relationship r = k(1 − ˝)n where r = dissolution rate, k = a rate constant, ˝ = relative saturation and n = the reaction order gave values of k = 1.72 × 10−10 mol cm−2 s−1 and n = 1.8 for the geometric surface area-normalised rates and k = 3.51 × 10−13 mol cm−2 s−1 and n = 1.8 for the BET surface area-normalised rates. In 196 day leaching column experiments trends in granule dissolution rate referenced to soil chemistry corresponded to predictions made by the SLIM model for dissolution of limestone in soil. If soil solution approaches saturation with respect to calcium carbonate granule dissolution will slow or even stop and granules be preserved indefinitely. Granules have the potential to be a small but significant component of the biogeochemical cycling of C and Ca in soil.

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This paper builds upon previous research on currency bands, and provides a model for the Colombian peso. Stochastic differential equations are combined with information related to the Colombian currency band to estimate competing models of the behaviour of the Colombian peso within the limits of the currency band. The resulting moments of the density function for the simulated returns describe adequately most of the characteristics of the sample returns data. The factor included to account for the intra-marginal intervention performed to drive the rate towards the Central Parity accounts only for 6.5% of the daily change, which supports the argument that intervention, if performed by the Central Bank, it is not directed to push the currency towards the limits. Moreover, the credibility of the Colombian Central Bank, Banco de la República’s ability to defend the band seems low.

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In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

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A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH(4)) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH oil the production of individual volatile fatty acids and CH, as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed oil CH(4) emission, with a maximum difference (across all forage types and all levels of DM 1) of 49 and 77% in g CH(4)/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0.1 and 0.4, respectively (values ranging from 10.2 to 19.5 g CH(4)/kg FCM). The lowest emission was established for early Cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH(4)/kg FCM declined oil average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0.1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0.4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH, emission per kg FCM mainly as a result of a higher DM I and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with COWS consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0.12 of the observed mean. Both observed and predicted emission expressed in g CH(4)/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH, emission in cattle sheds oil Dutch dairy farms and indicated that oil average a fraction of 0.28 of the total emissions must have originated from manure under these circumstances.

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Over many millions of years of independent evolution, placental, marsupial and monotreme mammals have diverged conspicuously in physiology, life history and reproductive ecology. The differences in life histories are particularly striking. Compared with placentals, marsupials exhibit shorter pregnancy, smaller size of offspring at birth and longer period of lactation in the pouch. Monotremes also exhibit short pregnancy, but incubate embryos in eggs, followed by a long period of post-hatching lactation. Using a large sample of mammalian species, we show that, remarkably, despite their very different life histories, the scaling of production rates is statistically indistinguishable across mammalian lineages. Apparently all mammals are subject to the same fundamental metabolic constraints on productivity, because they share similar body designs, vascular systems and costs of producing new tissue.

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Drawing upon an updated and expanded dataset of Energy Star and LEED labeled commercial offices, this paper investigates the effect of eco-labeling on rental rates, sale prices and occupancy rates. Using OLS and robust regression procedures, hedonic modeling is used to test whether the presence of an eco-label has a significant positive effect on rental rates, sale prices and occupancy rates. The study suggests that estimated coefficients can be sensitive to outlier treatment. For sale prices and occupancy rates, there are notable differences between estimated coefficients for OLS and robust regressions. The results suggest that both Energy Star and LEED offices obtain rental premiums of approximately 3%. A 17% sale price premium is estimated for Energy Star labeled offices but no significant sale price premium is estimated for LEED labeled offices. Surprisingly, no significant occupancy premium is estimated for Energy Star labeled offices and a negative occupancy premium is estimated for LEED labeled offices.

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This paper investigates the extent to which clients were able to influence performance measurement appraisals during the downturn in commercial property markets that began in the UK during the second half of 2007. The sharp change in market sentiment produced speculation that different client categories were attempting to influence their appraisers in different ways. In particular, it was recognised that the requirement for open-ended funds to meet redemptions gave them strong incentives to ensure that their asset values were marked down to market. Using data supplied by Investment Property Databank, we demonstrate that, indeed, unlisted open ended funds experienced sharper drops in capital values than other fund types in the second half of 2007, after the market turning point. These differences are statistically significant and cannot simply be explained by differences in portfolio composition. Client influence on appraisal forms one possible explanation of the results observed: the different pressures on fund managers resulting in different appraisal outcomes.

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Linear models of property market performance may be misspecified if there exist distinct states where the market drivers behave in different ways. This paper examines the applicability of non-linear regime-based models. A Self Exciting Threshold Autoregressive (SETAR) model is applied to property company share data, using the real rate of interest to define regimes. Distinct regimes appear exhibiting markedly different market behaviour. The model both casts doubt on the specification of conventional linear models and offers the possibility of developing effective trading rules for real estate equities.

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Motivation: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. Results: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method.

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Assimilation of temperature observations into an ocean model near the equator often results in a dynamically unbalanced state with unrealistic overturning circulations. The way in which these circulations arise from systematic errors in the model or its forcing is discussed. A scheme is proposed, based on the theory of state augmentation, which uses the departures of the model state from the observations to update slowly evolving bias fields. Results are summarized from an experiment applying this bias correction scheme to an ocean general circulation model. They show that the method produces more balanced analyses and a better fit to the temperature observations.

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Data assimilation aims to incorporate measured observations into a dynamical system model in order to produce accurate estimates of all the current (and future) state variables of the system. The optimal estimates minimize a variational principle and can be found using adjoint methods. The model equations are treated as strong constraints on the problem. In reality, the model does not represent the system behaviour exactly and errors arise due to lack of resolution and inaccuracies in physical parameters, boundary conditions and forcing terms. A technique for estimating systematic and time-correlated errors as part of the variational assimilation procedure is described here. The modified method determines a correction term that compensates for model error and leads to improved predictions of the system states. The technique is illustrated in two test cases. Applications to the 1-D nonlinear shallow water equations demonstrate the effectiveness of the new procedure.