scholarly journals On estimating the shape and dynamics of phenotypic distributions in ecology and evolution

2021 ◽  
Author(s):  
Brian Maitner ◽  
Aud Halbritter ◽  
Richard Telford ◽  
Tanya Strydom ◽  
Julia Chacon-Labella ◽  
...  
Keyword(s):  
Intraspecific Variation ◽  
Evolutionary Biology ◽  
R Package ◽  
Sampling Unit ◽  
Weighted Mean ◽  
Central Moments ◽  
Community Weighted Mean ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

scholarly journals Abnormal Portfolio Asset Allocation Model: Review

2020 ◽  
Vol 1 (1) ◽  
pp. 46-54
Author(s):  
Nurfadhlina Bt Abdul Halima ◽  
Dwi Susanti ◽  
Alit Kartiwa ◽  
Endang Soeryana Hasbullah
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Higher Moments ◽  
Investment Portfolio ◽  
Allocation Model ◽  
Model Review ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis ◽  
Normally Distributed

It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.

scholarly journals Contrasting adaptation and optimization of stomatal traits across communities at continental-scale

2021 ◽  
Author(s):  
Congcong Liu ◽  
Lawren Sack ◽  
Ying Li ◽  
Nianpeng He
Keyword(s):  
Niche Differentiation ◽  
Relative Importance ◽  
Ecosystem Productivity ◽  
Weighted Mean ◽  
Continental Scale ◽  
Community Weighted Mean ◽  
Use Efficiency ◽  
Stomatal Traits ◽  
Mean Variance ◽  
Maximum Stomatal Conductance

The maximum stomatal conductance (g), a major anatomical constraint on plant productivity, is a function of the stomatal area fraction (f) and stomatal space-use efficiency (e). However, f and g have been considered as equivalents, with e rarely considered, and their adaptation to the environment and their regulation of ecosystem productivity are unclear. Here, we analyzed the community-weighted mean, variance, skewness, and kurtosis of stomatal traits from tropical to cold-temperature forests. The variance of g and f was higher for arid sites, indicating greater functional niche differentiation, whereas that for e was lower, indicating convergence in efficiency. Besides, when other stomatal trait distributions remained unchanged, increasing kurtosis but decreasing skewness of g would improve ecosystem productivity, and f showed the opposite patterns. These findings highlight how the relative importance and equivalence of inter-related traits can differ at community scale.

scholarly journals The recurrence relations of order statistics moments for power Lomax distribution

2018 ◽  
Vol 52 (1) ◽  
pp. 75-90
Author(s):  
DEVENDRA KUMAR ◽  
SANKU DEY ◽  
MAZEN NASSAR ◽  
PREETI YADAV
Keyword(s):  
Bladder Cancer ◽  
Order Statistics ◽  
Recurrence Relations ◽  
Sample Sizes ◽  
Double Product ◽  
Cancer Data ◽  
Lomax Distribution ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis

The power Lomax distribution due to Rady et al. (2016) is an alternative to and provides better fits for bladder cancer data (Lee and Wang, 2003) than the Lomax, exponential Lo- max, Weibull Lomax, extended Poisson Lomax and beta Lomax distributions. Exact explicit expressions as well as recurrence relations for the single and double (product) moments have been derived from the power Lomax distribution. These recurrence relations enable computation of the mean, variance, skewness and kurtosis of all order statistics for all sample sizes in a simple and efficient manner. By using these relation, the mean, variance, skewness and kurtosis of order statistics for sample sizes up to 5 for various values of shape and scale parameters are tabulated. Finally, remission times (in months) of bladder cancer patients have been analyzed to show how the proposed relations work in practice.

scholarly journals Divergent Abiotic Stressors Drive Grassland Community Assembly of Tibet and Mongolia Plateau

2022 ◽  
Vol 12 ◽  
Author(s):  
Jianming Wang ◽  
Mingxu Li ◽  
Li Xu ◽  
Congcong Liu ◽  
Pu Yan ◽  
...  
Keyword(s):  
Community Assembly ◽  
Future Climate Change ◽  
Dry Matter Content ◽  
Grassland Community ◽  
Plant Trait ◽  
Abiotic Stressors ◽  
Trait Convergence ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis

Multiple ecological processes simultaneously govern community assembly, but it remains unclear how abiotic stressors regulate the relative importance of these processes among different biogeographic regions. Therefore, we conducted a comprehensive study on the responses of community assembly to varying environmental gradients, using the mean, variance, skewness, and kurtosis of plant height (height), specific leaf area (SLA) and leaf dry matter content (LDMC) distributions on the Tibetan Plateau (TP) and the Mongolian Plateau (MP). Our results showed that the prevalence of trait convergence across all grasslands in both TP and MP seem to be the result of abiotic filtering or weaker competitive exclusion etc. These trait-convergence assembly processes decrease the functional dispersion but increase the evenness of the trait frequency distribution. The mean, variance, skewness, and kurtosis responses of grassland communities to abiotic stress varied between the TP and MP. On average, plant trait distribution was mainly driven by temperature on the TP, and low-temperature stress altered the community assembly rules. In contrast, water availability shaped plant trait frequency distributions on the MP, and drought stress mediated the balance between different assembly processes. Our results provide empirical evidence that divergent abiotic stressors regulate the grassland community assembly on the TP and MP. Together, our study speculates that different aspects of future climate change, such as climate warming and changing precipitation patterns, on community assembly are dependent on regional climatic regimes.

scholarly journals vqtl: An R package for Mean-Variance QTL Mapping

2017 ◽  
Author(s):  
Robert W. Corty ◽  
William Valdar
Keyword(s):  
Qtl Mapping ◽  
Data Structures ◽  
Statistical Significance ◽  
R Package ◽  
Variance Heterogeneity ◽  
Genetic Loci ◽  
Genome Scans ◽  
Mapping Approach ◽  
The Mean ◽  
Mean Variance

ABSTRACTWe present vqtl, an R package for mean-variance QTL mapping. This QTL mapping approach tests for genetic loci that influence the mean of the phenotype, termed mean QTL, the variance of the phenotype, termed variance QTL, or some combination of the two, termed mean-variance QTL. It is unique in its ability to correct for variance heterogeneity arising not only from the QTL itself but also from nuisance factors, such as sex, batch, or housing. This package provides functions to conduct genome scans, run permutations to assess the statistical significance, and make informative plots to communicate results. Because it is inter-operable with the popular qtl package and uses many of the same data structures and input patterns, it will be straightforward for geneticists to analyze future experiments with vqtl as well as re-analyze past experiments, possibly discovering new QTL.

scholarly journals Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2421
Author(s):  
Roberta Fusco ◽  
Vincenza Granata ◽  
Mauro Mattace Raso ◽  
Paolo Vallone ◽  
Alessandro Pasquale De Rosa ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Univariate Analysis ◽  
Mean Value ◽  
Blood Oxygenation ◽  
Breast Lesions ◽  
Dce Mri ◽  
Malignant Lesions ◽  
The Mean ◽  
And Diffusion ◽  
Skewness And Kurtosis

Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.

scholarly journals New Methodology for Computing the Aircraft’s Position Based on the PPP Method in GPS and GLONASS Systems

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2525
Author(s):  
Kamil Krasuski ◽  
Damian Wierzbicki
Keyword(s):  
Linear Combination ◽  
Research Method ◽  
High Efficiency ◽  
Satellite System ◽  
Weighting Scheme ◽  
Measurement Technology ◽  
Dual Frequency ◽  
Weighted Mean ◽  
Mean Error ◽  
The Mean

In the field of air navigation, there is a constant pursuit for new navigation solutions for precise GNSS (Global Navigation Satellite System) positioning of aircraft. This study aims to present the results of research on the development of a new method for improving the performance of PPP (Precise Point Positioning) positioning in the GPS (Global Positioning System) and GLONASS (Globalnaja Nawigacionnaja Sputnikovaya Sistema) systems for air navigation. The research method is based on a linear combination of individual position solutions from the GPS and GLONASS systems. The paper shows a computational scheme based on the linear combination for geocentric XYZ coordinates of an aircraft. The algorithm of the new research method uses the weighted mean method to determine the resultant aircraft position. The research method was tested on GPS and GLONASS kinematic data from an airborne experiment carried out with a Seneca Piper PA34-200T aircraft at the Mielec airport. A dual-frequency dual-system GPS/GLONASS receiver was placed on-board the plane, which made it possible to record GNSS observations, which were then used to calculate the aircraft’s position in CSRS-PPP software. The calculated XYZ position coordinates from the CSRS-PPP software were then used in the weighted mean model’s developed optimization algorithm. The measurement weights are a function of the number of GPS and GLONASS satellites and the inverse of the mean error square. The obtained coordinates of aircraft from the research model were verified with the RTK-OTF solution. As a result of the research, the presented solution’s accuracy is better by 11–87% for the model with a weighting scheme as a function of the inverse of the mean error square. Moreover, using the XYZ position from the RTKLIB program, the research method’s accuracy increases from 45% to 82% for the model with a weighting scheme as a function of the inverse of the square of mean error. The developed method demonstrates high efficiency for improving the performance of GPS and GLONASS solutions for the PPP measurement technology in air navigation.

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