多重二元响应Probit模型的渐近有效估计

针对多重二元响应Probit模型提出了两步估计方法,第一步由边际似然得到参数√n相合的估计,第二步通过一步迭代得到渐近有效估计,由于只需一步迭代,因此在利用模拟方法计算信息阵时,可以增加模拟的次数,从而减少模拟所产生的扰动对估计的影响．     

植被层内能量与水分交换的显式解的推导

本文发展了一个求解植被－大气相互作用的稳态分层模式。它结合了Ｎｏｒｍａｎ提出的植被层内辐射能传输模型和Ｗａｓｓｏｎｅｒ及Ｒｅｉｆｓｎｙｄｅｒ提出的求解通量的电路类比模型,推导了来自空中及地表面辐射能在植被层内传递的显式解,还推导了一套通用的联立方程组,把植被层内显热及潜热通量、空气的温度及水汽压等表示为只是叶温的函数。结果避免了以往一些模型不必要迭代．减少了计算机工作量。     

具有年龄结构的接种流行病模型正平衡解的全局稳定性

研究一个具有年龄结构的接种SIS流行病模型正平衡解的稳定性,先利用等价积分方程给出了正平衡解存在的充分条件,再利用迭代方法及函数的单调性,得到了零平衡解与正平衡解全局稳定的充分条件。     

Fore-Iterative重建方法中迭代次数和子集数对SPM分析结果的影响

目的:探讨功能图像常用的三维重建方法Fore-Iterative中不同迭代次数和不同子集数目对统计参数图软件(SPM)统计比较结果的影响.方法:利用Hoffman标准脑模型进行PET成像与该模型制作的缺损模型进行PET成像后,采用临床常用参数进行三维重建,比较统计参数图(Statistical parametric mapping,SPM)的团体T检验结果.结果:(1)随着迭代次数的增加SPM得到的激活区增大,敏感度增加,差异显著性提高.(2)子集数目不同得到的激活区大小和假阳性不同,其中子集为32时得到的激活区最小,特异性最高.结论:迭代5次和子集数为32时使用SPM得到的结果最逼近真实值,产生较少的假阳性结果.     

一类扩散的种内相食系统正平衡态的全局渐近稳定性

讨论一类扩散的种内相食的捕食者-食饵模型,该模型带有齐次Neumann边界条件.通过迭代的方法证明:在适当的条件下,该模型唯一正常数平衡解全局渐近稳定.     

植被层内能量与水分交换的显式解的推导

本文发展了一个求解植被－大气相互作用的稳态分层模式。它结合了Ｎｏｒｍａｎ提出了植被层内辐射能传输模型和Ｗａｇｇｏｎｅｒ及Ｒｅｉｆｓｎｙｄｅｒ提出的求解通量的电路类比模型，推导了来自空中及地表面辐射能在植被层内传递的显式解，还推导了一套通用的联立方程组，把植被层内显热及潜热通量、空气的温度及水汽压等表示为只是叶温的函数。结果避免了以往一些模型不必要迭代，减少了计算机工作量。     

一类互惠生态模型解的周期性和爆破

研究了变系数两种群互惠模型解的周期性和爆破性.首先利用上下解和单调迭代方法研究了互惠模型周期解的存在性、稳定性和吸引性,结果表明种群之间的竞争强于互惠时周期解存在.接着利用比较原理得到了解在有限时刻爆破的充分条件,结果表明种群之间的互惠强于之间的竞争时爆破发生.最后通过数值模拟验证了定理的正确性.     

一类具连续时滞的三种群互助模型正平衡态的渐近稳定性

本文研究了一类具连续时滞的三种群互助模型,利用上、下解方法及相应的单调迭代方法,获得了该系统存在唯一正常数平衡态及该平衡态是全局渐近稳定的结论,为讨论时滞三种群模型提供了一种有效方法,所得结果也适用于二种群互助模型及不含时滞和扩散项的互助模型,因而推广了已有的一些结论．     

一类具有时空时滞的单种群模型行波解的存在性

通过单调迭代和上下解技术,研究了一类具有时空时滞的单物种种群模型行波解的存在性,证明了当时滞充分小时,方程具有连接两个平衡点的波前解,并得到了一些新的结果.     

遗传标记作图的通用最大似然模型

作者在构建连锁图谱时,发现Newton-Raphson迭代求解似然方程组,即便纳入合子和配子选择因子,各基因型的估计值仍不能很好的接近实测值,本文提出了一种偏分离遗传标记作图的通用最大似然模型。     

A minimal model of non-hyperbolic enzyme and receptor kinetics

A simplified version of P.W. Kühl's Recovery Model [Biochem. J. 298 (1994) 171-180] has been developed in which the duration of the recovery phase of receptor or enzyme (macro)molecule was assumed to be a random value distributed exponentially like other model parameters. The model has been shown to retain all the properties of the original Recovery Model except for its ability to yield asymmetric dose-response curves (if plotted in semi-logarithmic scale). Due to its simplicity, the present model is applicable for routine fitting to experimental data. In enzyme kinetics, the model yields a diversity of non-hyperbolic dose-response curves both with higher and lower steepness than that of Henri-type ones. In receptor kinetics, the diversity of dose-response curves is further increased due to virtually no restraints being imposed on the efficacies of any state of the macromolecule.     

Longitudinal random effects models for genetic analysis of binary data with application to mastitis in dairy cattle

A Bayesian analysis of longitudinal mastitis records obtained in the course of lactation was undertaken. Data were 3341 test-day binary records from 329 first lactation Holstein cows scored for mastitis at 14 and 30 days of lactation and every 30 days thereafter. First, the conditional probability of a sequence for a given cow was the product of the probabilities at each test-day. The probability of infection at time t for a cow was a normal integral, with its argument being a function of "fixed" and "random" effects and of time. Models for the latent normal variable included effects of: (1) year-month of test + a five-parameter linear regression function ("fixed", within age-season of calving) + genetic value of the cow + environmental effect peculiar to all records of the same cow + residual. (2) As in (1), but with five parameter random genetic regressions for each cow. (3) A hierarchical structure, where each of three parameters of the regression function for each cow followed a mixed effects linear model. Model 1 posterior mean of heritability was 0.05. Model 2 heritabilities were: 0.27, 0.05, 0.03 and 0.07 at days 14, 60, 120 and 305, respectively. Model 3 heritabilities were 0.57, 0.16, 0.06 and 0.18 at days 14, 60, 120 and 305, respectively. Bayes factors were: 0.011 (Model 1/Model 2), 0.017 (Model 1/Model 3) and 1.535 (Model 2/Model 3). The probability of mastitis for an "average" cow, using Model 2, was: 0.06, 0.05, 0.06 and 0.07 at days 14, 60, 120 and 305, respectively. Relaxing the conditional independence assumption via an autoregressive process (Model 2) improved the results slightly.     

Statistical modelling and forecasting annual sugarcane production in India: Using various time series models

This paper proposes a comparison of various time series forecasting models to forecast annual data on sugarcane production over 63 years from 1960 to 2022. In this research, the Mean Forecast Model, the Naive Model, the Simple Exponential Smoothing Model, Holt's model, and the Autoregressive Integrated Moving Average time series models have all been used to make effective and accurate predictions for sugarcane. Different scale-dependent error forecasting techniques and residual analysis have been used to examine the forecasting accuracy of these time series models. SE of Residuals, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Akaike's Information Criterion (AIC) are used to analyse the forecast's accuracy. The best model has been selected based on the predictions with the lowest value, according to the three-performance metrics of RMSE, MAE, and AIC. The estimated sugarcane production shows an increasing trend for the next 10 years and is projected to be 37,763.38 million tonnes in the year 2032. Further, empirical results support the plan and execution of viable strategies to advance sugarcane production in India to fulfil the utilisation need of the increasing population and further improve food security.     

度量误差对模型参数估计值的影响及参数估计方法的比较研究

基于模型V=aDb,首先在Matlab下用模拟实验的方法,研究了度量误差对模型参数估计的影响,结果表明:当V的误差固定而D的误差不断增大时,用通常最小二乘法对模型进行参数估计,参数a的估计值不断增大,参数b的估计值不断减小,参数估计值随着 D的度量误差的增大越来越远离参数真实值;然后对消除度量误差影响的参数估计方法进行研究,分别用回归校准法、模拟外推法和度量误差模型方法对V和D都有度量误差的数据进行参数估计,结果表明:回归校准法、模拟外推法和度量误差模型方法都能得到参数的无偏估计,克服了用通常最小二乘法进行估计造成的参数估计的系统偏差,结果进一步表明度量误差模型方法优于回归校准法和模拟外推法．     

Combined statistical and dynamical assessment of simulated vegetation–rainfall interactions in North Africa during the mid‐Holocene1

A negative feedback of vegetation cover on subsequent annual precipitation is simulated for the mid‐Holocene over North Africa using a fully coupled general circulation model with dynamic vegetation, FOAM‐LPJ (Fast Ocean Atmosphere Model‐Lund Potsdam Jena Model). By computing a vegetation feedback parameter based on lagged auto‐covariances, the simulated impact of North African vegetation on precipitation is statistically quantified. The feedback is also dynamically assessed through initial value ensemble experiments, in which North African grass cover is initially reduced and the climatic response analyzed. The statistical and dynamical assessments of the negative vegetation feedback agree in sign and relative magnitude for FOAM‐LPJ. The negative feedback on annual precipitation largely results from a competition between bare soil evaporation and plant transpiration, with increases in the former outweighing reductions in the latter given reduced grass cover. This negative feedback weakens and eventually reverses sign over time during a transient simulation from the mid‐Holocene to present. A similar, but weaker, negative feedback is identified in Community Climate System Model Version 2 (CCSM2) over North Africa for the mid‐Holocene.     

The CCPN data model for NMR spectroscopy: development of a software pipeline

To address data management and data exchange problems in the nuclear magnetic resonance (NMR) community, the Collaborative Computing Project for the NMR community (CCPN) created a "Data Model" that describes all the different types of information needed in an NMR structural study, from molecular structure and NMR parameters to coordinates. This paper describes the development of a set of software applications that use the Data Model and its associated libraries, thus validating the approach. These applications are freely available and provide a pipeline for high-throughput analysis of NMR data. Three programs work directly with the Data Model: CcpNmr Analysis, an entirely new analysis and interactive display program, the CcpNmr FormatConverter, which allows transfer of data from programs commonly used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment (Carnegie Mellon University), which was rewritten to interact directly with the Data Model. The ARIA 2.0 software for structure calculation (Institut Pasteur) and the QUEEN program for validation of restraints (University of Nijmegen) were extended to provide conversion of their data to the Data Model. During these developments the Data Model has been thoroughly tested and used, demonstrating that applications can successfully exchange data via the Data Model. The software architecture developed by CCPN is now ready for new developments, such as integration with additional software applications and extensions of the Data Model into other areas of research.     

Regeneration models and plant regenerative types related to the intensity of fire in Atlantic shrubland and woodland species

Question: Is it possible to model the germinative and resprouting behaviour of plant species in Atlantic shrublands and woodlands in relation to fire intensity? Is it possible to recognise different functional regenerative types in these plant species? Location: Galicia, NW Iberian Peninsula. Methods: We explored the patterns of germination and resprouting plant responses in relation to different intensities of fire using data from 37 trees, shrubs and herbaceous species growing in Atlantic shrublands and woodlands. Results: Synthesizing their germinative and resprouting behaviour, we created two graphical models: the Functional Germinative Model (FGM) and the Functional Sprouting Model (FSM). Integrating the germinative and resprouting responses, and taking into account fire intensity, we created the Functional Regenerative Model (FRM), which predicts the post‐fire recuperation of the populations of each species. The FRM has been validated with data from four Atlantic communities. We identified four plant functional regenerative types (PFRT) for Atlantic forest vegetation and we propose three intensities of response. Conclusions: The extracted models (FGM, FSM and FRM) and the grouping of species in four PFRTs could be applicable to more Atlantic species, to disturbance ecology in general and to population, community and landscape management.     

Evaluation of different models to describe egg and pupal development of Xyleborus fornicatus Eichh, （Coleoptera： Scolytidae）, the shot-hole borer of tea in Sri Lanka

Development data of eggs and pupae ofXyleborusfornicatus Eichh. （Coleoptera： Scolytidae）, the shot-hole borer of tea in Sri Lanka, at constant temperatures were used to evaluate a linear and seven nonlinear models for insect development. Model evaluation was based on fit to data （residual sum of squares and coefficient of determination or coefficient of nonlinear regression）, number of measurable parameters, the biological value of the fitted coefficients and accuracy in the estimation of thresholds. Of the nonlinear models, the Lactin model fitted experimental data well and along with the linear model, can be used to describe the temperature-dependent development of this species.     

A stochastic simulation study on using different models for prediction of breeding values while changing the breeding goal

In a stochastic simulation study the effect of simultaneously changing the model for prediction of breeding values and changing the breeding goal was studied. A population of 100 000 cows with registrations on seven traits was simulated in two steps. In the first step of 15 years the population was selected for production and mastitis occurrence using a univariate model for prediction of breeding values for production and a trivariate model using information on mastitis treatments, udder depth and somatic cell score for prediction of breeding values for mastitis occurrence. In the second step six different scenarios were set up and simulated for 15 years combining two different breeding goals and three different models for prediction of breeding values in 20 replicates. Breeding goal 1 had relative economic value per genetic standard deviation on production (19.4) and mastitis occurrence ( − 50) whereas breeding goal 2 had a economic value on production (19.4), udder depth (4.2), mastitis occurrence ( − 50), non return rate (13.0) and days open ( − 16.75). Model 1 was a model similar to the one used in the first 15 years. Model 2 was an approximate multitrait model where solutions for fixed effects from a model corresponding to model 1 were subtracted from the phenotypes and a multitrait model with an overall mean, a year effect, an additive genetic and a residual effect were applied. Model 3 was a full multitrait model. Average genetic trends for total merit and each individual trait over 20 replicates were compared for each scenario. With the number of replicates the genetic responses using model 2 and 3 were not significant different. With a broad breeding goal using, model 2 or model 3 gave a significantly higher response in total merit than using model 1. Using a narrow breeding goal there was no significant difference between models used for prediction of breeding values. Results showed that with a breeding goal with a lot of emphasis on low heritable traits with a high economic value using a multitrait methodology for prediction of breeding values will redistribute the genetic progress in the total merit index. More gain will come from the low heritable traits in the breeding goal and less from traits with higher heritability. With a broad breeding goal and exploiting the available information in the data the inbreeding coefficient increased though not significantly.