Estimating Within-Locus Nonadditive Coefficient and Discriminating Dominance Versus Overdominance as the Genetic Cause of Heterosis

Genetics ◽  
1998 ◽  
Vol 148 (4) ◽  
pp. 2003-2014
Author(s):  
Hong-Wen Deng

Abstract Testing (over)dominance as the genetic cause of heterosis and estimating the (over)dominance coefficient (h) are related. Using simulations, we investigate the statistical properties of Mukai's approach, which is intended to estimate the average (h¯) of hi across loci by regression of outcrossed progeny on the sum of the two corresponding homozygous parents. A new approach for estimating h¯ is also developed, utilizing data on families formed by multiple selfed genotypes from each outcrossed parent, thus not requiring constructing homozygotes. Assuming constant mutation effects, h can be estimated accurately by both approaches under dominance. When rare alleles have low frequencies at any polymorphic locus, Mukai's approach can estimate h accurately under over(under)dominance. Therefore, the (over)dominance hypothesis for heterosis can be tested by estimating h, under either dominance or overdominance at all genomic loci. However, this is invalid with more plausible mixed dominance and overdominance at different loci. Estimating the variance of hi across loci is also investigated. In self-compatible outcrossing populations with mutations of variable effects and lethals, our new approach is better than Mukai's, not only because of not requiring homozygotes but also because of the better statistical performance reflected by the smaller mean square errors of the estimates.

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Abdullah Y. Al-Hossain ◽  
Mursala Khan

To obtain the best estimates of the unknown population parameters have been the key theme of the statisticians. In the present paper we have suggested some estimators which estimate the population parameters efficiently. In short we propose a ratio, product, and regression estimators using two auxiliary variables, when there are some maximum and minimum values of the study and auxiliary variables, respectively. The properties of the proposed strategies in terms of mean square errors (variances) are derived up to first order of approximation. Also the performance of the proposed estimators have shown theoretically and these theoretical conditions are verified numerically by taking four real data sets under which the proposed class of estimators performed better than the other previous works.


2019 ◽  
Vol 11 (3) ◽  
pp. 273-284
Author(s):  
M. R. Hasan

The main objective of this paper is to find the minimax estimator of the scale parameter of Laplace distribution under MLINEX loss function by applying the theorem of Lehmann (1950). The estimator is then compared with classical estimator like moment estimator with respect to mean square errors (MSEs) through R- Code simulation. The result has shown that the minimax estimator under MLINEX loss function is better than moment estimator for all sample sizes. Finally, mean square errors of different estimators corresponding to sample size are presented graphically.


2020 ◽  
pp. 1-45
Author(s):  
Zhigao Wang ◽  
Xianyi Wu ◽  
Chunjuan Qiu

Abstract The projection of outstanding liabilities caused by incurred losses or claims has played a fundamental role in general insurance operations. Loss reserving methods based on individual losses generally perform better than those based on aggregate losses. This study uses a parametric individual information model taking not only individual losses but also individual information such as age, gender, and so on from policies themselves into account. Based on this model, this study proposes a computation procedure for the projection of the outstanding liabilities, discusses the estimation and statistical properties of the unknown parameters, and explores the asymptotic behaviors of the resulting loss reserving as the portfolio size approaching infinity. Most importantly, this study demonstrates the benefits of individual information on loss reserving. Remarkably, the accuracy gained from individual information is much greater than that from considering individual losses. Therefore, it is highly recommended to use individual information in loss reserving in general insurance.


Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.


2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.


2021 ◽  
pp. 1-14
Author(s):  
Noura Hamze ◽  
Lukas Nocker ◽  
Nikolaus Rauch ◽  
Markus Walzthöni ◽  
Matthias Harders ◽  
...  

BACKGROUND: Accurate segmentation of connective soft tissues in medical images is very challenging, hampering the generation of geometric models for bio-mechanical computations. Alternatively, one could predict ligament insertion sites and then approximate the shapes, based on anatomical knowledge and morphological studies. OBJECTIVE: In this work, we describe an integrated framework for automatic modelling of human musculoskeletal ligaments. METHOD: We combine statistical shape modelling with geometric algorithms to automatically identify insertion sites, based on which geometric surface/volume meshes are created. As clinical use case, the framework has been applied to generate models of the forearm interosseous membrane. Ligament insertion sites in the statistical model were defined according to anatomical predictions following a published approach. RESULTS: For evaluation we compared the generated sites, as well as the ligament shapes, to data obtained from a cadaveric study, involving five forearms with 15 ligaments. Our framework permitted the creation of models approximating ligaments’ shapes with good fidelity. However, we found that the statistical model trained with the state-of-the-art prediction of the insertion sites was not always reliable. Average mean square errors as well as Hausdorff distances of the meshes could increase by an order of magnitude, as compared to employing known insertion locations of the cadaveric study. Using those, an average mean square error of 0.59 mm and an average Hausdorff distance of less than 7 mm resulted, for all ligaments. CONCLUSIONS: The presented approach for automatic generation of ligament shapes from insertion points appears to be feasible but the detection of the insertion sites with a SSM is too inaccurate, thus making a patient-specific approach necessary.


Author(s):  
Pavle Šćepanović ◽  
Frederik A. Döring

AbstractFor a broad range of applications, flight mechanics simulator models have to accurately predict the aircraft dynamics. However, the development and improvement of such models is a difficult and time consuming process. This is especially true for helicopters. In this paper, two rapidly applicable and implementable methods to derive linear input filters that improve the simulator model are presented. The first method is based on model inversion, the second on feedback control. Both methods are evaluated in the time domain, compared to recorded helicopter flight test data, and assessed based on root mean square errors and the Qualification Test Guide bounds. The best results were achieved when using the first method.


1944 ◽  
Vol 7 (53) ◽  
pp. 279-294
Author(s):  
G. H. Menzies

2017 ◽  
Vol 10 (5) ◽  
pp. 1813-1821
Author(s):  
Pengfei Xia ◽  
Shirong Ye ◽  
Kecai Jiang ◽  
Dezhong Chen

Abstract. In the GPS radio occultation technique, the atmospheric excess phase (AEP) can be used to derive the refractivity, which is an important quantity in numerical weather prediction. The AEP is conventionally estimated based on GPS double-difference or single-difference techniques. These two techniques, however, rely on the reference data in the data processing, increasing the complexity of computation. In this study, an undifferenced (ND) processing strategy is proposed to estimate the AEP. To begin with, we use PANDA (Positioning and Navigation Data Analyst) software to perform the precise orbit determination (POD) for the purpose of acquiring the position and velocity of the mass centre of the COSMIC (The Constellation Observing System for Meteorology, Ionosphere and Climate) satellites and the corresponding receiver clock offset. The bending angles, refractivity and dry temperature profiles are derived from the estimated AEP using Radio Occultation Processing Package (ROPP) software. The ND method is validated by the COSMIC products in typical rising and setting occultation events. Results indicate that rms (root mean square) errors of relative refractivity differences between undifferenced and atmospheric profiles (atmPrf) provided by UCAR/CDAAC (University Corporation for Atmospheric Research/COSMIC Data Analysis and Archive Centre) are better than 4 and 3 % in rising and setting occultation events respectively. In addition, we also compare the relative refractivity bias between ND-derived methods and atmPrf profiles of globally distributed 200 COSMIC occultation events on 12 December 2013. The statistical results indicate that the average rms relative refractivity deviation between ND-derived and COSMIC profiles is better than 2 % in the rising occultation event and better than 1.7 % in the setting occultation event. Moreover, the observed COSMIC refractivity profiles from ND processing strategy are further validated using European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data, and the results indicate that the undifferenced method reduces the noise level on the excess phase paths in the lower troposphere compared to the single-difference processing strategy.


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