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本文研究讨论了在单性状模型下几种方差组分估计方法,它们是:极大似然法(ML)、约束极大似然法(REML)、最小二乘无偏估计(MINQUE)、最小方差二乘无偏估计以及 Henderson 的第3法等。其中MINQUE和REML法的估计误差最小,但MINQUE的收敛速度高于REML。Henderson 第3法和ML对误差方差均为有偏估计,因此它们的估计误最大;MINQUE法实质上就是REML估计,因此在实际应用中多采用MINQUE和REML法。 相似文献
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四、方差组分的其它估计方法除了极大似然法外,还有许多方法,如MIVQUE、MINQUE以及Henderson法等。下面我们将作一简单介绍。 (一)MINQUE法根据Henderson的算法,MINQUE估计方差组分的公式为: 相似文献
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以鲁西黄牛和渤海黑牛（各30头）12个微卫星座位数据为基础,利用系统树分析法、最大似然法及Bayes方法,比较不同方法对个体识别效率的影响。结果表明：当利用12个微卫星座位和6个低杂合度位点数据时,3种个体识别方法鉴定的准确性均为100%。但利用6个高杂合度座位时,Bayes方法的准确性最高（83.33%）,最大似然法次之（76.67%）,系统树分析法最低（71.67%）。结果表明,基于Bayes理论的个体识别方法最准确,是进行同类研究的首选工具,而系统树分析法和最大似然法可以作为其补充加以应用。 相似文献
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用MTDFREML估计中国美利奴羊(新疆型)产毛性状的遗传参数 总被引：1，自引：0，他引：1
利用新疆巩乃斯种羊场饲养的2001-2005年出生的5 425只中国美利奴羊(新疆型)周岁资料,采用动物模型多性状非求导约束最大似然法(MTDFREML),估计了中国美利奴羊(新疆型)在新疆自然条件下产毛性状的遗传参数.结果表明:毛长度、剪毛后体重、产毛量和纤维直径的遗传力估计值分别为0.13、0.29、0.22和0.36. 相似文献
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《畜牧兽医学报》2016,(9)
本研究旨在对出生于2008-2013年的中国西门塔尔牛肉用群体的重要经济性状进行遗传参数和方差组分估计,该群体大小为2 939头。采用非求导约束最大似然法估计遗传力、遗传相关和方差组分。结果显示,初生重、断奶重、出栏重、胴体重、屠宰率和净肉率的遗传力估计值分别为0.48、0.44、0.43、0.38、0.31、0.39。其中,初生重和断奶重的遗传相关估计结果为0.57,出栏重和胴体重的遗传相关为0.94,屠宰率和净肉率的遗传相关为0.89。该群体的生长和屠宰相关性状均属于中高遗传力性状,且性状之间具有较高的遗传相关。本研究对中国西门塔尔牛肉用群体重要经济性状的遗传参数做了系统评估分析,为将来制定育种方案和遗传评估奠定基础。 相似文献
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利用极大似然估计值评定饲料营养价值 总被引：1，自引：0，他引：1
本文作者提出了利用极大似然估计值评定饲料营养价值的方法，并说明了这种估计值是最佳线性无偏估计值和用于评定饲料营养价值的可行性，举出实例说明了方法的应用。 相似文献
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对敖汉细毛羊早期性状遗传参数估计的研究 《畜牧与饲料科学》2015,36(12):83-83
运用动物模型BLUP法(最佳线性无偏预测法)和MTDFREML法(多性状非求导约束最大似然法)对敖汉细毛羊的早期性状进行了分析,得出了初生重、断乳重和周岁重的遗传力,并就遗传参数估计结果进行了讨论。 相似文献
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家蚕标记基因位点与数量性状基因位点重组参数的最大似然估计法 总被引：8，自引：2，他引：6
利用分离世代群体（ＢＣ＿１或Ｆ＿２），估算家蚕标记基因位点与数量性状基因位点重组参数的最大似然估计法，求解似然方程组的ＥＭ迭代算法。通过１２０次计算机模拟和一个生产实例验证了方法的可行性。 相似文献
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Comparison of restricted maximum likelihood and method R for estimating heritability and predicting breeding value under selection 总被引：3，自引：0，他引：3
Cantet RJ Birchmeier AN Santos-Cristal MG de Avila VS 《Journal of animal science》2000,78(10):2554-2560
Method R and Restricted Maximum Likelihood (REML) were compared for estimating heritability (h2) and subsequent prediction of breeding values (a) with data subject to selection. A single-trait animal model was used to generate the data and to predict breeding values. The data originated from 10 sires and 100 dams and simulation progressed for 10 overlapping generations. In simulating the data, genetic evaluation used the underlying parameter values and sires and dams were chosen by truncation selection for greatest predicted breeding values. Four alternative pedigree structures were evaluated: complete pedigree information, 50% of phenotypes with sire identities missing, 50% of phenotypes with dam identities missing, and 50% of phenotypes with sire and dams identities missing. Under selection and with complete pedigree data, Method R was a slightly less consistent estimator of h2 than REML. Estimates of h2 by both methods were biased downward when there was selection and loss of pedigree information and were unbiased when no selection was practiced. The empirical mean square error (EMSE) of Method R was several times larger than the EMSE of REML. In a subsequent analysis, different combinations of generations selected and generations sampled were simulated in an effort to disentangle the effects of both factors on Method R estimates of h2. It was observed that Method R overestimated h2 when both the sampling that is intrinsic in the method and the selection occurred in generations 6 to 10. In a final experiment, BLUP(a) were predicted with h2 estimated by either Method R or REML. Subsequently, five more generations of selection were practiced, and the mean square error of prediction (MSEP) of BLUP(a) was calculated with estimated h2 by either method, or the true value of the parameter. The MSEP of empirical BLUP(a) using Method R was greater than the MSEP of empirical BLUP(a) using REML. The latter statistic was closer to prediction error variance of BLUP(a) than the MSEP of empirical BLUP(a) using Method R, indicating that empirical BLUP(a) calculated using REML produced accurate predictions of breeding values under selection. In conclusion, the variability of h2 estimates calculated with Method R was greater than the variability of h2 estimates calculated with REML, with or without selection. Also, the MSEP of EBLUP(a) calculated using estimates of h2 by Method R was larger than MSEP of EBLUP(a) calculated with REML estimates of h2. 相似文献
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In cross-over designs, individual sequences of treatments are applied to the animals. Within such designs it is possible that every treatment could modify the effect of the subsequent treatment applied to the same animal. We compared three cross-over designs each with three treatments, three periods, and two blocks. This comparison was done with respect to the variance of the estimations of the effects and its biases caused by the interactions between the treatment and the carry over effect of the foregoing treatment. Moreover, different methods of estimating variance components and calculating the degrees of freedom were compared by means of simulation. If the animal variance component is small, then the bias of the REML estimator of the variance components is greater than one of the widespread ANOVA-estimator called 'TYPE3'. But nevertheless, the mean squared error of this estimation is smaller in the case of REML in comparison to ANOVA. Therefore, the REML method should be preferred. For calculating the degrees of freedom, the Kenward-Roger method should be used. After applying this method, the true significance level is almost equal to its required value, but if the Satterthwaite method is used, the true significance level will be too high. If the interaction (treatment x carry over) is ignored in the model although it exists, the standard error of the treatment effect estimation is too great, and, therefore, the true significance level is too small. The methods which have been evaluated are available in the SAS-procedure MIXED (SAS Institute, 1999a). To assist the investigation of cross-over designs by using this software, we developed programs for data management and data analysis. These programs are available from the first author. 相似文献
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M. Leppaänen K. Maäki J. Juga H. Saloniemi 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2000,117(2):97-103
The heritability of hip dysplasia in the German Shepherd Dog was estimated by applying the animal model and the Restricted Maximum Likelihood (REML) method to a data-set which consisted of the hip scores of 10 335 dogs. Fixed effects of the model were the month and the year of birth, screening age, the panelist responsible for screening and the origin of the animal's sire. The litter and the breeder had only minor effects on hip joints. Heritability estimates were moderate (0.31–0.35). The moderate heritability, which was found in this study, enables a much better genetic gain in the breeding programme, if proper evaluation methods, such as BLUP animal model, and effective selection is used instead of phenotypic selection. 相似文献
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ByM. Leppänen K. Mäki J. Juga H. Saloniemi 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2000,117(3):97-103
The heritability of hip dysplasia in the German Shepherd Dog was estimated by applying the animal model and the Restricted Maximum Likelihood (REML) method to a data‐set which consisted of the hip scores of 10335 dogs. Fixed effects of the model were the month and the year of birth, screening age, the panelist responsible for screening and the origin of the animal's sire. The litter and the breeder had only minor effects on hip joints. Heritability estimates were moderate (0.31–0.35). The moderate heritability, which was found in this study, enables a much better genetic gain in the breeding programme, if proper evaluation methods, such as BLUP animal model, and effective selection is used instead of phenotypic selection. 相似文献
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SUMMARY: Patterson and Thompson's idea of 'error contrasts' (or restricted maximum likelihood) (1971) was extended to multiple sets of linear contrasts for variance component estimtion. The error contrasts were established in such a way that only errors are retained in the model. The error variance was then estimated by maximizing the likelihood function obtained from the error contrasts. More sets of linear contrasts were then progressively established such that each set of linear contrasts contains only one class of random effects and the errors. A likelihood function was constructed and maximized for each variance of random effects given the error variance held at its estimated value. The likelihood function for estimating the covariance component between two classes of random effects was established such that all other random effects are treated as fixed effects. The likelihood function was then maximized with respect to the covariance given the two variance components fixed at their estimated values. The multidimensional optimization problem in the traditional restricted maximum-likelihood problem was then turned into several one-dimensional optimization problems by using this technique. Inasmuch as the error variance was estimated using a partial likelihood function and the other variance components are estimated using likelihood functions conditional on the estimated error variance, the method is referred to as partial and conditional maximum likelihood (PCML). ZUSAMMENFASSUNG: Partielle und bedingte Maximum Likelihood zur Sch?tzung von Varianzkomponenten Die Patterson und Thompson Vorstellungen von 'Fehlerkontrasten' (1971) (oder beschr?nkte maximale Likelihood) wurde auf multiple Gruppen linearer Kontraste für Varianzkomponenten- sch?tzung ausgedehnt. Die Fehlerkontraste erfolgen in der Form, da? nur Fehler im Modell verbleiben. Die Fehlervarianz wurde dann durch Maximierung der Likelihood Funktion von Fehlerkontrasten gesch?tzt. Weitere Gruppen linearer Kontraste wurden nacheinander etabliert dergestalt, da? jede Gruppe linearer Kontraste nur eine Klasse zuf?lliger Wirkungen und die Fehler enth?lt. Eine Likelihood Funktion wurde konstruiert und für jede Varianz von Zufallsgr??en maximiert unter der Voraussetzung, da? die Fehlervarianz auf ihrem gesch?tzten Wert verbleibt. Die Likelihood Funktion zur Sch?tzung der Ko-Varianzkomponenten zwischen zwei Klassen zuf?lliger Wirkungen wurde in der Form aufgestellt, da? alle anderen Zufallswirkungen als fixe behandelt werden. Die Likelihood Funktion wurde maximiert im Hinblick auf Ko-Varianz bei gegebenen gesch?tzten Varianzkomponenten. Das multidimensionale Optimierungsproblem der traditionellen restringierten Maximum Likelihood wurde auf diese Weise in ein eindimensionales Optimierungsproblem verwandelt. Nachdem die Fehlervarianz aus der partiellen Likelihood Funktion und die anderen Varianzkomponenten unter Verwendung der bedingten Likelihood Funktionen gesch?tzt worden waren, wurde die Methode als partielle und bedingte Maximum Likelihood (pcml) bezeichnet. 相似文献
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C. Wittwer H. Hamann E. Rosenberger & O. Distl 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2007,124(5):302-307
Heritabilities were estimated for osteochondrosis (OC) in fetlock and hock joints and palmar/plantar osseous fragments in fetlock joints of South German Coldblood (SGC) horses using Residual Maximum Likelihood (REML) under a linear animal model. The analyses were based on the results of a standardized radiographic examination of 167 SGC horses with a mean age of 14 months. The heritabilities linearly estimated and transformed onto the liability scale were for OC in fetlock joints 0.16 and for OC in hock joints 0.04. Considering fetlock and hock OC together, results in a heritability of 0.17. Palmar/plantar osseus fragments of the fetlock joints showed a heritability of 0.48. We concluded that there is most likely a genetic component in the variation of the development of osteochondrosis in fetlock and hock joints as well as for palmar/plantar osseus fragments of fetlock joints of the investigated population of SGC horses. 相似文献
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Assessment of carcass composition based on ultrasonic measurements and EUROP conformation class of live lambs 总被引：1，自引：0，他引：1
M-L. Puntila K. Mäki O. Rintala 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2002,119(6):367-378
Summary The aim of this study was to investigate the accuracy of ultrasound muscle (UMD) and fat depth (UFD) measurements as well as live EUROP conformation class (LEUROP) in predicting carcass composition and conformation in lambs. Measurements of 5993 lambs were analysed applying a multi‐trait animal model and the Restricted Maximum Likelihood (REML) method to obtain variance components for scanning live weight (SLW), UMD, UFD and LEUROP. The data were field records of Finnsheep and a small number of lambs from other breeds, from over 30 flocks between 1997 and 1999. The lambs were measured close to 120 days of age. Scanning was behind the last rib and at the third lumbar vertebra. Just before slaughter, scanning was repeated with a subset of lambs, whose half carcasses (n = 224) were dissected for lean, fat and bone. The UMD (third lumbar) and SLW together accounted for 51% of the variance in lean weight in the model in Finnsheep. The UFD alone explained 21% of the variance in lean percentage, UMD was a better predictor for carcass conformation than LEUROP. The estimates of heritability for SLW, UMD, UFD and LEUROP were 0.44, 0.46, 0.39 and 0.27 (with standard errors of 0.03 each), respectively. High positive genetic correlations, ranging from 0.49 to 0.69, were obtained between the four traits. Selection for UMD has resulted in genetic improvement of 0.06 mm/year (1%) in a Finnsheep nucleus flock. Conformation score of live animals could be considered to be included in the breeding programme if uniformity of assessment is assured by continued training. 相似文献
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L. Rönnegård R. Al-Sarraj & D. von Rosen 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2009,126(2):110-116
In variance component quantitative trait loci (QTL) analysis, a mixed model is used to detect the most likely chromosome position of a QTL. The putative QTL is included as a random effect and a method is needed to estimate the QTL variance. The standard estimation method used is an iterative method based on the restricted maximum likelihood (REML). In this paper, we present a novel non-iterative variance component estimation method. This method is based on Henderson's method 3, but relaxes the condition of unbiasedness. Two similar estimators were compared, which were developed from two different partitions of the sum of squares in Henderson's method 3. The approach was compared with REML on data from a European wild boar × domestic pig intercross. A meat quality trait was studied on chromosome 6 where a functional gene was known to be located. Both partitions resulted in estimated QTL variances close to the REML estimates. From the non-iterative estimates, we could also compute good approximations of the likelihood ratio curve on the studied chromosome. 相似文献
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1. Genetic and residual variances and covariances were estimated on performance data from 5943 laying hens from a 7 generation selection experiment for the traits: egg number up to day 270 (EN270), egg weight (EW), body weight at day 215 (BW), egg mass 100 g of food (EMFC), and residual food consumption (RFC) by a Henderson 3 and REML procedure.
2. Simultaneous REML estimates of all 30 components were obtained by a software package is based on numerical optimisation of the log likelihood using a multivariate animal model. Henderson 3 estimates were computed on the basis of a hierarchical sire‐dam model. Estimates were generated beginning with a data set comprising only the first generation, and then successively adding one generation after the other.
3. REML estimates for heritabilities h 2 on the basis of all performance records were 0.40, 0.75, 0.62, 0.21 and 0.22 for traits EN270, EW, BW, EMFC, and RFC, respectively. The corresponding Henderson 3 estimates were: 0.30, 0.57, 0.43, 0.21, and 0.20.
4. The results indicate that some REML h 2 estimates are substantially different from those obtained by Henderson 3 once the data set included three generations as opposed to those based on Henderson 3. 相似文献
20.
1. Direct versus indirect selection for food conversion ratio of growth (FCR) after selection for live body weight (LWT), a sequential scheme often applied in broilers, was considered. In the present study loss of response in either FCR or aggregate genotype (H) when LWT was included was investigated under selection on a linear index of ratio component traits (and LWT) or FCR (and LWT) by selection index methodology.
2. Relative responses in FCR and H were generally very similar under single‐step and sequential selection. Without LWT in H, selection for linear index or ratio gave similar responses in FCR when heritabilities of components were equal. With large differences in heritabilities (0.2 compared with 0.5) or genetic and environmental correlation (>0.6) significant differences in response (5 to 12%) in FCR emerged. Therefore, whether additional costs are justified for parameter and breeding value estimation when using a linear index in place of selection for the ratio depends on the difference in heritabilities and correlations of the ratio component traits. With LWT in H, loss of response in FCR was partially or entirely offset by response in LWT.
3. The non‐normality of FCR and consequences for (co)variance component estimation were studied in terms of the coefficients of variation of the component traits of FCR. Restricted Maximum Likelihood (REML) estimation of (co)variance components for both FCR and logarithm transformed FCR (closer to normality) showed the robustness of REML to such deviations from normality. 相似文献