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Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date. 相似文献
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基于马尔科夫链蒙特卡洛(简记为MCMC)模拟的参数贝叶斯估计,对改进的广义帕累托分布(简记为MGPD)模型进行了优化,并利用该模型得到了地质灾害损失的在险损失值(简记为VaR)和条件损失值(简记为CVaR).以湖南娄底市地质灾害损失数据进行实证分析及模型适应性检验,结果表明:优化后的模型不仅具有很好的极值数据描述能力,而且具有较强的适用性. 相似文献
4.
基于信号博弈的阳澄湖大闸蟹绿色标签市场应用分析 总被引:2,自引:0,他引:2
水产品绿色标签对消费者来说是高质量的信号,对卖家来说则是卖出高价的资本.但是欺诈行为的存在损害了消费者和其他卖家的利益,扰乱了市场秩序.以阳澄湖大闸蟹为例,通过信号博彝理论,对螃蟹市场中关卖双方的消费行为进行博彝分析,得到了精炼贝叶斯Nash均衡. 相似文献
5.
《Veterinary parasitology》2015,207(1-2):1-6
The success of a Toxoplasma gondii surveillance program in European pig production systems depends partly on the quality of the test to detect infection in the population. The test accuracy of a recently developed serological bead-based assay (BBA) was investigated earlier using sera from experimentally infected animals. In this study, the accuracy of the BBA was determined by the use of sera from animals from two field subpopulations. As no T. gondii infection information of these animals was available, test accuracy was determined through a Bayesian approach allowing for conditional dependency between BBA and an ELISA test. The priors for prevalence were based on available information from literature, whereas for specificity vague non-informative priors were used. Priors for sensitivity were based either on available information or specified as non-informative. Posterior estimates for BBA sensitivity and specificity were (mode) 0.855 (Bayesian 95% credibility interval (bCI) 0.702–0.960) and 0.913 (bCI 0.893–0.931), respectively. Comparing the results of BBA and ELISA, sensitivity was higher for the BBA while specificity was higher for ELISA. Alternative priors for the sensitivity affected posterior estimates for sensitivity of both BBA and ELISA, but not for specificity. Because the difference in prevalence between the two subpopulations is small, and the number of infected animals is small as well, the precision of the posterior estimates for sensitivity may be less accurate in comparison to the estimates for specificity. The estimated value for specificity of BBA is at least optimally defined for testing pigs from conventional and organic Dutch farms. 相似文献
6.
基于拐点集合判别的TBUD方法主要思路是分析拐点集合间的关系,并在高维空间进行划分,从而搭建判别模型,并将分析框架应用在特质波动率等若干指标上,利用实证数据得到结论。应用TBUD判别框架可以发现,特质波动率等指标无法对拐点集合进行清晰划分,因而并不具有预测能力。 相似文献
7.
New sugarcane cultivars are continuously developed to improve sugar industry productivity. Despite this sugarcane crop models such as the ‘Sugar’ module in the Agricultural Productions System sIMulator (APSIM-Sugar) have not been updated to reflect the most recent cultivars. The implications of misrepresenting cultivar parameters in APSIM-Sugar is difficult to judge as little research has been published on the likely values of these parameters and how uncertainty in parameter values may affect model outputs. A global sensitivity analysis can be used to better understand how cultivar parameters influence simulated yields. A Gaussian emulator was used to perform a global sensitivity analysis on simulated biomass and sucrose yield at harvest for two contrasting sugarcane-growing regions in Queensland, Australia. Biomass and sucrose yields were simulated for 42 years to identify inter-annual variability in output sensitivities to 10 parameters that represent physiological traits and can be used to simulated differences between sugarcane cultivars. Parameter main effect (Si) and total effect (STi) sensitivity indices and emulator accuracy were calculated for all year-region-output combinations. When both regions were considered together parameters representing radiation use efficiency (rue), number of green leaves (green_leaf_no) and a conductance surrogate parameter (kL) were the most influential parameters for simulated biomass in APSIM-Sugar. Simulated sucrose yield was most sensitive to rue, sucrose_fraction (representing the fraction of biomass partitioned as sucrose in the stem) and green_leaf_no. However, climate and soil differences between regions changed the level of influence cultivar parameters had on simulation outputs. Specifically, model outputs were more sensitive to changes in the transp_eff_cf and kL parameters in the Burdekin region due to lower rainfall and poor simulated soil conditions. Collecting data on influential traits that are relatively simple to measure (e.g. number of green leaves) during cultivar development would greatly contribute to the simulation of new cultivars in crop models. Influential parameters that are difficult to measure directly such as transp_eff_cf and sucrose_fraction are ideal candidates for statistical calibration. Calibrating crop models either through direct observation or statistical calibration would allow crop modellers to better test how new cultivars will perform in a range of production environments. 相似文献
8.
A field calibration experiment was carried out on salt‐affected clayey soil in Syria, to compare the sensitivity to soil electrical conductivity (ECe), and bulk density (ρb) of two instruments for estimating soil moisture: the neutron probe (NP) and the Diviner 2000 capacitance probe (CP). The results showed that the values of the correlation coefficient of the calibration were decreased when the ECe and ρb values increased; this decrease was more pronounced for the Diviner 2000, indicating that it was more sensitive to ρb and ECe than the NP. When only scaled frequency was used in the fitted equation, the Diviner 2000 in wet soil underestimated soil water content significantly at all depths, but especially in the top layer, by up to 0.09 cm3/cm3 compared with gravimetric determinations. However, in dry soil, the Diviner 2000 overestimated the volumetric water content by up to 0.05 cm3/cm3 in the top 15 cm, and by 0.03 cm3/cm3 at 30‐45 cm depth. The performance of the neutron probe was better overall; using a factory calibration curve no significant differences were observed between NP estimates and the gravimetric values. Including both ρb and ECe in the calibration equations improved the fits, although the regression coefficient (R2) for the Diviner 2000 remained low. 相似文献
9.
Fernando Brito Lopes Fernando Baldi Ludmilla Costa Brunes Marcos Fernando Oliveira e Costa Eduardo da Costa Eifert Guilherme Jordão Magalhães Rosa Raysildo Barbosa Lobo Cláudio Ulhoa Magnabosco 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2023,140(1):1-12
This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale. 相似文献
10.
The two methods of estimating parameter in computable general equilibrium(CGE) model are introduced and compared:the calibration procedure and econometric estimation. The conclusions are:the estimation of parameter in CGE model must use the calibration procedure coupled with the econometric estimation method;the elasticity of output with respect to labor input,the marginal expenditure share for households and price elasticity of export demand are estimated by econometric estimation method;and other parameters of the CGE model can be get by calibration procedure. 相似文献