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Wittenburg D Guiard V Teuscher F Reinsch N 《Animal : an international journal of animal bioscience》2008,2(11):1559-1568
Genetics affects not only the weight of piglets at birth but also the variability of birth weight within litter. Previous studies on this topic assigned the sample standard deviation of piglet birth weights within litter as an observation to the sow. However, the contribution of the difference in mean birth weight per sex on the within-litter variance has been neglected so far. This work deals with the genetic effect on within-litter variance when different statistical models with different distributional assumptions are used and considers the sex effect and appropriate weights per trait. Traits were formed from the pooled sample variance of male and female birth weights within litter. A linear model approach was fitted to the logarithmized within-litter variance and the sample standard deviation. A generalized linear model with gamma-distributed residuals and log-link function was applied to the untransformed sample variance. Models were compared by analysing data from 9439 litters from Landrace and Large White of a commercial breeding programme. The estimates of heritability for different traits ranged from 7% to 11%. Although the generalized linear mixed model is preferred from a mathematical view, the rank correlations between breeding values of the linear mixed models and the generalized linear mixed model were relatively high, i.e. 94% to 98%. By residual diagnostics, a linear mixed model using the weighted and pooled within-litter standard deviation was identified as most suitable. 相似文献
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A log gamma model and its maximum likelihood estimation 总被引：4，自引：0，他引：4
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René P. Widmer Stephen J. Ferguson 《Computer methods in biomechanics and biomedical engineering》2013,16(8):908-922
To characterise the flow of a fluid through a uniform porous medium, the medium may be completely described by its permeability, a measure of flow resistance. Fluid flow in the intertrabecular spaces of cancellous bone has been recognised as an important factor in a number of physical phenomena. In order to investigate the interdependence of permeability, porosity and the structural parameters, we adapted a morphological model and systematically varied its structural parameters. By simulating a viscous Stokes flow regime, we were able to estimate the anisotropic permeability tensor and performed an extensive, stepwise multivariate regression analysis to establish empirical relationships between the morphological parameters and the permeability for the anatomical directions individually. The regression analysis indicated high values of determination coefficients [0.88 < R2 < 0.89 (transversal directions) and R2 = 0.60 (longitudinal direction), porosity-based prediction and R2 = 0.98 for all directions and information presented to the regression model]. We conclude that a pooled set of structural parameters may explain up to 98% of the permeability variability, the regression model predicts permeability values that match experimental data, and a good prediction performance could be achieved by only incorporating the porosity and either the degree of anisotropy (0.89 < R2 < 0.91) or the trabecular spacing predictor (0.96 < R2 < 0.97). These conclusions imply that trabecular thickness and shape parameters only play a minor role in the determination of vertebral trabecular bone permeability. However, a major limitation of the model is that it reflects an idealisation of the real, regionally varying structure of trabecular bone. Therefore, the goodness-of-fit estimates we are presenting should be considered as an upper bound limitation regarding the prediction performance. 相似文献
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The robust design is a method for implementing a mark-recapture experiment featuring a nested sampling structure. The first level consists of primary sampling sessions; the population experiences mortality and immigration between primary sessions so that open population models apply at this level. The second level of sampling has a short mark-recapture study within each primary session. Closed population models are used at this stage to estimate the animal abundance at each primary session. This article suggests a loglinear technique to fit the robust design. Loglinear models for the analysis of mark-recapture data from closed and open populations are first reviewed. These two types of models are then combined to analyze the data from a robust design. The proposed loglinear approach to the robust design allows incorporating parameters for a heterogeneity in the capture probabilities of the units within each primary session. Temporary emigration out of the study area can also be accounted for in the loglinear framework. The analysis is relatively simple; it relies on a large Poisson regression with the vector of frequencies of the capture histories as dependent variable. An example concerned with the estimation of abundance and survival of the red-back vole in an area of southeastern Québec is presented. 相似文献
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We applied the grey system theory to evaluation of chlorophyll (Chl) degradation in Chamaecyparis Sieb. & Zucc. var. formosana (Hayata) Rehder needle-leaf in the Yuanyang Lake Nature Preserve of northern Taiwan. Pigment analysis was finished within 12 h after collecting the samples. Four grey prediction models for the degradation of Chl a, Chl b, and for the change of Chl a/b ratio and water content were established and compared with the results of linear and exponential regression analysis. The residual error and accuracy range show that the grey prediction process is much better than regression analysis. The degradation of Chl a and b contains two phases, one being fast and the other slow. 相似文献
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A Morgenstern-type bivariate gamma distribution 总被引：1，自引：0，他引：1
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Abstract: We perceive a need for more complete interpretation of regression models published in the wildlife literature to minimize the appearance of poor models and to maximize the extraction of information from good models. Accordingly, we offer this primer on interpretation of parameters in single- and multi-variable regression models. Using examples from the wildlife literature, we illustrate how to interpret linear zero-intercept, simple linear, semi-log, log-log, and polynomial models based on intercepts, coefficients, and shapes of relationships. We show how intercepts and coefficients have biological and management interpretations. We examine multiple linear regression models and show how to use the signs (+, -) of coefficients to assess the merit and meaning of a derived model. We discuss 3 methods of viewing the output of 3-dimensional models (y, x1, x2) in 2-dimensional space (sheet of paper) and illustrate graphical model interpretation with a 4-dimensional logistic regression model. Statistical significance or Akaike best-ness does not prevent the appearance of implausible regression models. We recommend that members of the peer review process be sensitive to full interpretation of regression models to forestall bad models and maximize information retrieval from good models 相似文献
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比较3个应用较广的模拟物种地理分布模型:广义线性模型(GLM)、广义加法模型(GAM)与分类回归树(CART)对中国树种地理分布模拟的优劣,以提出更为合适的模拟物种地理分布模型,并用于预测气候变化对物种地理分布的影响。3个模型对中国15种树种地理分布的模拟研究表明:除对油松、辽东栎分布的模拟精度稍差外,对其余树种分布的模拟精度均较高,其中以GAM模型最好。结合地理信息系统(GIS),比较分析了这3个模型对青冈、木荷、红松和油松4种树种的地理分布模拟效果,结果亦表明:这3个模型均能很好模拟青冈和木荷的地理分布,而GLM模型对红松分布的模拟结果不太理想,3个模型对油松分布的模拟结果均不甚理想,其中以GLM模型最差。基于3个模型对未来气候变化下青冈与蒙古栎地理分布的预测表明:GLM模型与GAM模型对青冈分布的预测结果较为接近,青冈在未来气候变化情景下向西和向北扩展,而CART模型预测青冈在未来气候变化情景下除有向西、向北扩展趋势外,广东和广西南部的青冈分布区将消失;3个模型均预测蒙古栎在未来气候变化情景下向西扩展,扩展面积的大小为:模型的模拟面积>模型>模型。 相似文献
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《Current biology : CB》2020,30(8):1555-1561.e4
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In clinical trials, the comparison of two different populations is a common problem. Nonlinear (parametric) regression models are commonly used to describe the relationship between covariates, such as concentration or dose, and a response variable in the two groups. In some situations, it is reasonable to assume some model parameters to be the same, for instance, the placebo effect or the maximum treatment effect. In this paper, we develop a (parametric) bootstrap test to establish the similarity of two regression curves sharing some common parameters. We show by theoretical arguments and by means of a simulation study that the new test controls its significance level and achieves a reasonable power. Moreover, it is demonstrated that under the assumption of common parameters, a considerably more powerful test can be constructed compared with the test that does not use this assumption. Finally, we illustrate the potential applications of the new methodology by a clinical trial example. 相似文献
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Wagner PJ 《Biology letters》2012,8(1):143-146
Rate distributions are important considerations when testing hypotheses about morphological evolution or phylogeny. They also have implications about general processes underlying character evolution. Molecular systematists often assume that rates are Poisson processes with gamma distributions. However, morphological change is the product of multiple probabilistic processes and should theoretically be affected by hierarchical integration of characters. Both factors predict lognormal rate distributions. Here, a simple inverse modelling approach assesses the best single-rate, gamma and lognormal models given observed character compatibility for 115 invertebrate groups. Tests reject the single-rate model for nearly all cases. Moreover, the lognormal outperforms the gamma for character change rates and (especially) state derivation rates. The latter in particular is consistent with integration affecting morphological character evolution. 相似文献
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Ecological studies aim to analyse the variation of disease risk in relation to exposure variables that are measured at an area unit level. In practice it is rarely possible to use the exposure variables themselves, either because the corresponding data are not available or because the causes of the disease are not fully understood. It is therefore quite common to use crude proxies of the real exposure to the disease in question. These proxies are rarely able to explain the disease variation and hence additional area level random effects are introduced to account for the residual variation. In this paper we investigate the possibility to model the effect of ecological covariates non‐parametrically, with and without additional random effects for the residual spatial variation. We illustrate the issues arising through analyses of simulated and real data on larynx cancer mortality in Germany, during the years of 1986 to 1990, where we use the corresponding lung cancer rates as a proxy for smoking consumption. 相似文献
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昆虫发育进度的非正态描述──分段指数曲线 总被引：1，自引：0，他引：1
提出了分段连续指数曲线转化为多元线性回归方程的方法。利用取剩余平方和最小的方法确定未知折点。给出了在描述昆虫发育进度的模拟模型。 相似文献
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Aims Preserving and restoring Tamarix ramosissima is urgently required in the Tarim Basin, Northwest China. Using species distribution models to predict the biogeographical distribution of species is regularly used in conservation and other management activities. However, the uncertainty in the data and models inevitably reduces their prediction power. The major purpose of this study is to assess the impacts of predictor variables and species distribution models on simulating T. ramosissima distribution, to explore the relationships between predictor variables and species distribution models and to model the potential distribution of T. ramosissima in this basin.Methods Three models—the generalized linear model (GLM), classification and regression tree (CART) and Random Forests—were selected and were processed on the BIOMOD platform. The presence/absence data of T. ramosissima in the Tarim Basin, which were calculated from vegetation maps, were used as response variables. Climate, soil and digital elevation model (DEM) data variables were divided into four datasets and then used as predictors. The four datasets were (i) climate variables, (ii) soil, climate and DEM variables, (iii) principal component analysis (PCA)-based climate variables and (iv) PCA-based soil, climate and DEM variables.Important findings The results indicate that predictive variables for species distribution models should be chosen carefully, because too many predictors can reduce the prediction power. The effectiveness of using PCA to reduce the correlation among predictors and enhance the modelling power depends on the chosen predictor variables and models. Our results implied that it is better to reduce the correlating predictors before model processing. The Random Forests model was more precise than the GLM and CART models. The best model for T. ramosissima was the Random Forests model with climate predictors alone. Soil variables considered in this study could not significantly improve the model's prediction accuracy for T. ramosissima. The potential distribution area of T. ramosissima in the Tarim Basin is ~3.57 × 10 4 km 2, which has the potential to mitigate global warming and produce bioenergy through restoring T. ramosissima in the Tarim Basin. 相似文献
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Wiemann MC Manchester SR Dilcher DL Hinojosa LF Wheeler EA 《American journal of botany》1998,85(12):1796-1802
The utility of regression and correspondence models for deducing climate from leaf physiognomy was evaluated by the comparative application of different predictive models to the same three leaf assemblages. Mean annual temperature (MAT), mean annual precipitation (MAP), and growing season precipitation (GSP) were estimated from the morphological characteristics of samples of living leaves from two extant forests and an assemblage of fossil leaves. The extant forests are located near Gainesville, Florida, and in the Florida Keys; the fossils were collected from the Eocene Clarno Nut Beds, Oregon. Simple linear regression (SLR), multiple linear regression (MLR), and canonical correspondence analysis (CCA) were used to estimate temperature and precipitation. The SLR models used only the percentage of species having entire leaf margins as a predictor for MAT and leaf size as a predictor for MAP. The MLR models used from two to six leaf characters as predictors, and the CCA used 31 characters. In comparisons between actual and predicted values for the extant forests, errors in prediction of MAT were 0.6°-5.7°C, and errors in prediction of precipitation were 6-89 cm (=6-66%). At the Gainesville site, seven models underestimated MAT and only one overestimated it, whereas at the Keys site, all eight models overestimated MAT. Precipitation was overestimated by all four models at Gainesville, and by three of them at the Keys. The MAT estimates from the Clarno leaf assemblage ranged from 14.3° to 18.8°C, and the precipitation estimates from 227 to 363 cm for MAP and from 195 to 295 cm for GSP. 相似文献