931 resultados para success models comparison
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We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.
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Blast fragmentation can have a significant impact on the profitability of a mine. An optimum run of mine (ROM) size distribution is required to maximise the performance of downstream processes. If this fragmentation size distribution can be modelled and controlled, the operation will have made a significant advancement towards improving its performance. Blast fragmentation modelling is an important step in Mine to Mill™ optimisation. It allows the estimation of blast fragmentation distributions for a number of different rock mass, blast geometry, and explosive parameters. These distributions can then be modelled in downstream mining and milling processes to determine the optimum blast design. When a blast hole is detonated rock breakage occurs in two different stress regions - compressive and tensile. In the-first region, compressive stress waves form a 'crushed zone' directly adjacent to the blast hole. The second region, termed the 'cracked zone', occurs outside the crush one. The widely used Kuz-Ram model does not recognise these two blast regions. In the Kuz-Ram model the mean fragment size from the blast is approximated and is then used to estimate the remaining size distribution. Experience has shown that this model predicts the coarse end reasonably accurately, but it can significantly underestimate the amount of fines generated. As part of the Australian Mineral Industries Research Association (AMIRA) P483A Mine to Mill™ project, the Two-Component Model (TCM) and Crush Zone Model (CZM), developed by the Julius Kruttschnitt Mineral Research Centre (JKMRC), were compared and evaluated to measured ROM fragmentation distributions. An important criteria for this comparison was the variation of model results from measured ROM in the-fine to intermediate section (1-100 mm) of the fragmentation curve. This region of the distribution is important for Mine to Mill™ optimisation. The comparison of modelled and Split ROM fragmentation distributions has been conducted in harder ores (UCS greater than 80 MPa). Further work involves modelling softer ores. The comparisons will be continued with future site surveys to increase confidence in the comparison of the CZM and TCM to Split results. Stochastic fragmentation modelling will then be conducted to take into account variation of input parameters. A window of possible fragmentation distributions can be compared to those obtained by Split . Following this work, an improved fragmentation model will be developed in response to these findings.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.
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This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.
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This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.
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Ghosh's model is discussed in this paper under two alternative scenarios. In an open version we compare it with Leontief's model and prove that they reduce to each other under some specific productive conditions. We then move onto reconsidering Ghosh's model alleged implausibility and we do so reformulating the model to incorporate a closure rule. The closure solves, to some extent, the implausibility problem very clearly put out by Oosterhaven for then value-added is correctly computed and responsive to allocation changes resulting from supply shocks.
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The purpose of this paper is to provide a comparative analysis of pork value chains in Catalonia, Spain and Manitoba, Canada. Intensive hog production models were implemented in Catalonia in the 1960s as a result of agriculture crises and fostered by feedstuffs factories. The expansion of the hog sector in Manitoba is more recent (in the 1990s) and brought about in large part by the opening of the Maple Leaf Meats processing plant in Brandon, Manitoba. This plant is capable of processing 90,000 hogs per week. Both hog production models ‐ the ‘older’ one in Catalonia (Spain) and the ‘newer’ in Manitoba‐ have been, until recently, examples of success. Inventories and production have been increasing substantially and both regions have proven to have great export potential. Recently, however, tensions have been developing with the hog production models of both regions, particularly as they relate to environmental concerns. The purpose of the paper is to compare the value chains with respect to their origins (e.g. supply a growing demand for pork, ensure farm profitability) and present states (e.g. environmental concerns, profitability). Keywords: pork value chain, hog farms, agri‐food studies. JEL: Q10, Q13, O57
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BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.
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BACKGROUND Persistence of anti-tumor necrosis factor (TNF) therapy in rheumatoid arthritis (RA) is an overall marker of treatment success. OBJECTIVE To assess the survival of anti-TNF treatment and to define the potential predictors of drug discontinuation in RA, in order to verify the adequacy of current practices. DESIGN An observational, descriptive, longitudinal, retrospective study. SETTING The Hospital Clínico Universitario de Valladolid, Valladolid, Spain. PATIENTS RA patients treated with anti-TNF therapy between January 2011 and January 2012. MEASUREMENTS Demographic information and therapy assessments were gathered from medical and pharmaceutical records. Data is expressed as means (standard deviations) for quantitative variables and frequency distribution for qualitative variables. Kaplan-Meier survival analysis was used to assess persistence, and Cox multivariate regression models were used to assess potential predictors of treatment discontinuation. RESULTS In total, 126 treatment series with infliximab (n = 53), etanercept (n = 51) or adalimumab (n = 22) were administered to 91 patients. Infliximab has mostly been used as a first-line treatment, but it was the drug with the shortest time until a change of treatment. Significant predictors of drug survival were: age; the anti-TNF agent; and the previous response to an anti-TNF drug. LIMITATION The small sample size. CONCLUSION The overall efficacy of anti-TNF drugs diminishes with time, with infliximab having the shortest time until a change of treatment. The management of biologic therapy in patients with RA should be reconsidered in order to achieve disease control with a reduction in costs.
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A Comparison of the Management Models of Protected Areas between China and the African South Region allows reading and evaluating the similarities and differences in the use of management model as a management tool for protected areas in China and South African Region. Specifically, some positive and negative features of the management approaches for the two regions. Secondary data was collected from various related literature such as policy documents, students‟ dissertations/thesis, scientific articles and magazines. Based on the method above, the study found out that China's first nature reserve was the Dingus Mountain Nature Reserve in Zhaoqing, Guangdong province established in 1956. By the end of 2005, about 2,349 nature reserves of various kinds were set up throughout the country, covering a total area of 149.95 million ha and accounting for 15 percent of the total land territory. The study further found that Southern Africa has approximately 4,390 protected areas out of 11487920 total land areas and Eastern Africa has approximately 1838144 protected areas, which is equivalent to 15.0% of the total land areas. South Africa in this region had its first declared natural park in 1926 after Paul Kruger (a war hero) had alerted the authorities of the extinguishing threat of some animal species of region.
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OBJECTIVE To compare the health assistance models of Basic Traditional Units (UBS) with the Family Health Strategy (ESF) units for presence and extent of attributes of Primary Health Care (APS), specifically in the care of children. METHOD A cross-sectional study of a quantitative approach with families of children attended by the Public Health Service of Colombo, Paraná. The Primary Care Assessment Tool (PCA-Tool) was applied to parents of 482 children, 235 ESF units and 247 UBS units covering all primary care units of the municipality, between June and July 2012. The results were analyzed according to the PCA-Tool manual. RESULTS ESF units reached a borderline overall score for primary health care standards. However, they fared better in their attributes of Affiliation, Integration of care coordination, Comprehensiveness, Family Centeredness and Accessibility of use, while the attributes of Community Guidance/Orientation, Coordination of Information Systems, Longitudinality and Access attributes were rated as insufficient for APS. UBS units had low scores on all attributes. CONCLUSION The ESF units are closer to the principles of APS (Primary Health Care), but there is need to review actions of child care aimed at the attributes of APS in both care models, corroborating similar studies from other regions of Brazil.
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Selostus: Lannoituksen pitkäaikaiset kenttäkokeet: kolmen matemaattisen mallin vertailu
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The intensity correlation functions C(t) for the colored-gain-noise model of dye lasers are analyzed and compared with those for the loss-noise model. For correlation times ¿ larger than the deterministic relaxation time td, we show with the use of the adiabatic approximation that C(t) values coincide for both models. For small correlation times we use a method that provides explicit expressions of non-Markovian correlation functions, approximating simultaneously short- and long-time behaviors. Comparison with numerical simulations shows excellent results simultaneously for short- and long-time regimes. It is found that, when the correlation time of the noise increases, differences between the gain- and loss-noise models tend to disappear. The decay of C(t) for both models can be described by a time scale that approaches the deterministic relaxation time. However, in contrast with the loss-noise model, a secondary time scale remains for large times for the gain-noise model, which could allow one to distinguish between both models.