In this study,we propose a Gram-Charlier expansion approach to investigate the impact of skewness and kurtosis on production and hedging decisions.Consistent with the existing literature,we find that skewness and kurt...In this study,we propose a Gram-Charlier expansion approach to investigate the impact of skewness and kurtosis on production and hedging decisions.Consistent with the existing literature,we find that skewness and kurtosis do not affect decisions regarding optimal production;however,they significantly influence optimal hedging decisions.We observe that positive skewness with platykurtic spot prices or negative skewness with leptokurtic spot prices often leads to over-hedging when the initial forward contract price exceeds its expected value.Conversely,under-hedging is expected when the initial forward contract price falls below its expected value.In other conditions,skewness can either promote or impede speculative future trading.Using the Gram-Charlier expansion of the spot price density function,we find that optimal future positions depend on forward prices,the hedgers’risk preference,and the spot price distribution.Simulations validate our findings on the impact of skewness and kurtosis on future hedging.Finally,we analyze of a cotton storage and forward contracting dataset to illustrate the application of our methodology and support our theoretical results.展开更多
The skewness of subsurface temperature anomaly in the equatorial Pacific Ocean shows a significant asymmetry between the east and west. A positive temperature skewness appears in the equatorial eastern Pacific, while ...The skewness of subsurface temperature anomaly in the equatorial Pacific Ocean shows a significant asymmetry between the east and west. A positive temperature skewness appears in the equatorial eastern Pacific, while the temperature skewness in the western and central Pacific is primarily negative. There is also an asymmetry of the temperature skewness above and below the climatological mean therrnocline in the central and western Pacific. A positive skewness appears below the thermocline, but the skewness is negative above the thermocline. The distinctive vertical asymmetry of the temperature skewness is argued to be attributed to the asymmetric temperature response to upward and downward thermocline displacement in the presence of the observed upper-ocean vertical thermal structure. Because of positive （negative） second derivative of temperature with respect to depth below （above） the thermocline, an upward and a downward shift of the thermocline with equal displacement would lead to a negative temperature skewness above the thermocline but a positive skewness below the thermocline. In the far eastern equatorial Pacific, the thermocline is close to the base of the mixed layer, the shape of the upper-ocean vertical temperature profile cannot be kept. Positive skewness appears in both below the thermocline and above the thermocline in the far eastern basin. Over the central and eastern Pacific, the anomalies of the subsurface waters tend to entrain into the surface mixed layer （by climatological mean upwelling） and then affect the SST. Hence, the positive （negative） subsurface skewness in the far eastern （central） Pacific may favor positive （negative） SST skewness, which is consistent with the observational fact that more La Nina （EI Nino） occur in the central （eastern） Pacific. The present result implies a possible new paradigm for EI Nino and La Nina amplitude asymmetry in the eastern Pacific.展开更多
Using nonequilibrium statistical mechanics closure method, it is shown that the skewness factor of the velocity derivative of isotropic turbulence ap- proaches a constant -0.515 when the Reynolds number is very high, ...Using nonequilibrium statistical mechanics closure method, it is shown that the skewness factor of the velocity derivative of isotropic turbulence ap- proaches a constant -0.515 when the Reynolds number is very high, which is in agree- ment with the DNS (direct numerical simulation) result of Vincent and Meneguzzi (1991).展开更多
Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades...Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this paper, we propose and study a novel class of models： a skew-normal mixture of joint location, scale and skewness models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The issues of maximum likelihood estimation are addressed. In particular, an Expectation-Maximization （EM） algorithm for estimating the model parameters is developed. Properties of the estimators of the regression coefficients are evaluated through Monte Carlo experiments. Results from the analysis of a real data set from the Body Mass Index （BMI） data are presented.展开更多
In this study, the statistical powers of Kolmogorov-Smimov two-sample （KS-2） and Wald Wolfowitz （WW） tests, non-parametric tests used in testing data from two independent samples, have been compared in terms of fi...In this study, the statistical powers of Kolmogorov-Smimov two-sample （KS-2） and Wald Wolfowitz （WW） tests, non-parametric tests used in testing data from two independent samples, have been compared in terms of fixed skewness and fixed kurtosis by means of Monte Carlo simulation. This comparison has been made when the ratio of variance is two as well as with equal and different sample sizes for large sample volumes. The sample used in the study is： （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 25）, （50, 50）, （50, 75）, （50, 100）, （75, 25）, （75, 50）, （75, 75）, （75, 100）, （100, 25）, （100, 50）, （100, 75）, and （100, 100）. According to the results of the study, it has been observed that the statistical power of both tests decreases when the coefficient of kurtosis is held fixed and the coefficient of skewness is reduced while it increases when the coefficient of skewness is held fixed and the coefficient of kurtosis is reduced. When the ratio of skewness is reduced in the case of fixed kurtosis, the WW test is stronger in sample volumes （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 75）, and （50, 100） while KS-2 test is stronger in other sample volumes. When the ratio of kurtosis is reduced in the case of fixed skewness, the statistical power of WW test is stronger in volume samples （25, 25）, （25, 75）, （25, 100）, and （75, 25） while KS-2 test is stronger in other sample volumes.展开更多
The turbulence governed by the Navier-Stokes equation is paramount in many physical processes.However,it has been considered as a challenging problem due to its inherent nonlinearity,non-equilibrium,and complexity.Her...The turbulence governed by the Navier-Stokes equation is paramount in many physical processes.However,it has been considered as a challenging problem due to its inherent nonlinearity,non-equilibrium,and complexity.Herein,we review the connections between the velocity derivative skewness Sk and the non-equilibrium properties of turbulence.Sk,a reasonable candidate for describing the non-equilibrium turbulence,which varies during the non-equilibrium procedure.A lot of experimental or numerical evidences have shown that the perturbation of energy spectrum,which associated with the excitation of large scales,results in an obvious variation of Sk,and Sk is a negative value in this rapid energy decay process.The variation of positive Sk is closely related to the perturbation of transfer spectrum,and this corresponds to the backward energy transfer process.In addition,the skewness characterizes the production(or reduction)rate of enstrophy due to vortex stretching(or compression).Using the transport equation of turbulent energy dissipation rate and enstrophy,it is possible to establish a theoretical connection between skewness and the non-equilibrium turbulence.It is expected that this work could trigger the rapid advancement of the future studies of non-equilibrium turbulence,and also the improvement of turbulence models.展开更多
Non-Gaussian random vibrations have gained more attention in the dynamics-research community due to the frequently encountered non-Gaussian dynamic environments in engineering practice.This work proposes a novel non-G...Non-Gaussian random vibrations have gained more attention in the dynamics-research community due to the frequently encountered non-Gaussian dynamic environments in engineering practice.This work proposes a novel non-Gaussian random vibration test method by simultaneous control of multiple correlation coefficients,skewness,and kurtoses.The multi-channel time-domain coupling model is first constructed which is mainly composed of the designed parameters and independent signal sources.The designed parameters are related to the defined correlation coefficients and root mean square values.The synthesized multiple non-Gaussian random signals are unitized to provide independent signal sources for coupling.The first four statistical characteristics of the synthesized non-Gaussian random signals are theoretically derived so that the relationships among the generated signals,independent signal sources,and correlation coefficients are achieved.Subsequently,a multi-channel closed-loop equalization procedure for non-Gaussian random vibration control is presented to produce a multi-channel correlated non-Gaussian random vibration environment.Finally,a simulation example and an experimental verification are provided.Results from the simulation and experiment indicate that the multi-channel response spectral densities,correlation coefficients,skewnesses,and kurtoses can be stably and effectively controlled within the corresponding tolerances by the proposed method.展开更多
Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice. One reason for this may be ...Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice. One reason for this may be the lack of dissemination and further exploration of this new measure. Additionally, the authors focused mainly on specific probability distributions. One of the advantages of AS is that it considers the entire shape of the distribution, rather than focusing only on moments or the linear distance between central tendency statistics or quantiles. This holistic approach makes AS particularly robust in cases where the distribution deviates from normality or contains outliers. This paper aims to generalize its use to random samples with either known or unknown distributions. The study has three objectives: 1) to develop an R script for point and interval estimation of AS;2) to provide interpretive norms of normality by examining normality in bootstrap sampling distributions;and 3) to compare asymptotic and bootstrap standard errors. Interval estimation is approached asymptotically and through bootstrap. The script was illustrated using two examples: one with generated data and another with real-world data. Interpretive norms of normality are derived from 40 samples of various sizes, created by inverse transform sampling to follow a standard normal distribution. Bootstrap intervals at three confidence levels (0.9, 0.95, and 0.99) were obtained using the normal method, with two exceptions: the bias-corrected and accelerated percentile method for the 60-data sample and the percentile method for the 600-data sample, as these deviated from normality. Asymptotic 95% confidence intervals are also provided. The asymptotic standard error was larger than the bootstrap one, with the difference decreasing as the sample size increased. The script is concluded to have practical and educational utility for estimating AS, whose asymptotic sampling distribution is normal.展开更多
The skewness of the return distribution is one of the important features of the security price.In this paper,the authors try to explore the relationship between the skewness and the coefficient ofrisk premium.The coef...The skewness of the return distribution is one of the important features of the security price.In this paper,the authors try to explore the relationship between the skewness and the coefficient ofrisk premium.The coefficient of the risk premium is estimated by a GARCH-M model,and the robustmeasurement of skewness is calculated by Groeneveld-Meeden method.The empirical evidences forthe composite indexes from 33 securities markets in the world indicate that the risk compensationrequirement in the market where the return distribution is positively skewed is virtually zero,andthe risk compensation requirement is positive in a significant level in the market where the returndistribution is negative skewed.Moreover,the skewness is negatively correlated with the coefficient ofthe risk premium.展开更多
Variable selection is an important research topic in modern statistics, traditional variable selection methods can only select the mean model and(or) the variance model, and cannot be used to select the joint mean, va...Variable selection is an important research topic in modern statistics, traditional variable selection methods can only select the mean model and(or) the variance model, and cannot be used to select the joint mean, variance and skewness models. In this paper, the authors propose the joint location, scale and skewness models when the data set under consideration involves asymmetric outcomes,and consider the problem of variable selection for our proposed models. Based on an efficient unified penalized likelihood method, the consistency and the oracle property of the penalized estimators are established. The authors develop the variable selection procedure for the proposed joint models, which can efficiently simultaneously estimate and select important variables in location model, scale model and skewness model. Simulation studies and body mass index data analysis are presented to illustrate the proposed methods.展开更多
The skewness of a graph G is the minimum number of edges in G whose removal results in a planar graph. In this paper, we determine the skewness of the generalized Petersen graph P（4k, k） and hence a lower bound for ...The skewness of a graph G is the minimum number of edges in G whose removal results in a planar graph. In this paper, we determine the skewness of the generalized Petersen graph P（4k, k） and hence a lower bound for the crossing number of P（4k, k）. In addition, an upper bound for the crossing number of P（4k, k） is also given.展开更多
Reinforcement learning as autonomous learning is greatly driving artificial intelligence(AI)development to practical applications.Having demonstrated the potential to significantly improve synchronously parallel learn...Reinforcement learning as autonomous learning is greatly driving artificial intelligence(AI)development to practical applications.Having demonstrated the potential to significantly improve synchronously parallel learning,the parallel computing based asynchronous advantage actor-critic(A3C)opens a new door for reinforcement learning.Unfortunately,the acceleration's influence on A3C robustness has been largely overlooked.In this paper,we perform the first robustness assessment of A3C based on parallel computing.By perceiving the policy's action,we construct a global matrix of action probability deviation and define two novel measures of skewness and sparseness to form an integral robustness measure.Based on such static assessment,we then develop a dynamic robustness assessing algorithm through situational whole-space state sampling of changing episodes.Extensive experiments with different combinations of agent number and learning rate are implemented on an A3C-based pathfinding application,demonstrating that our proposed robustness assessment can effectively measure the robustness of A3C,which can achieve an accuracy of 83.3%.展开更多
Under probability weighting,entrepreneurs with skewness preference tend to seek rightskewed and avoid left-skewed risks.We show that Chinese firms managed by CEOs with professional epidemic experience,i.e.,who previou...Under probability weighting,entrepreneurs with skewness preference tend to seek rightskewed and avoid left-skewed risks.We show that Chinese firms managed by CEOs with professional epidemic experience,i.e.,who previously experienced the outbreak of SARS during their tenure as high level executives,have a lower stock price crash risk measured by the negative skewness of stock prices in subsequent periods.In particular,those firms intentionally avoid stock price crashes by adopting more conservative strategies in decisionmaking.Overall,we provide the first evidence on the unintended effect of entrepreneurs'subjective judgments of the probabilities of disease outbreaks on financial market stability.These have long-term implications for the financial system.展开更多
In this paper, we propose a new approach to the test of elliptical symmetry based on theprojection pursuit (P.P.) technique, the number-theoretic method, skewness and kurtosis. Thelimiting null distributions of the ne...In this paper, we propose a new approach to the test of elliptical symmetry based on theprojection pursuit (P.P.) technique, the number-theoretic method, skewness and kurtosis. Thelimiting null distributions of the new statistics are derived. The powers of the tests against sixalternatives are calculated by simulation, which shows that the new t.st's are acceptable.展开更多
We use transaction-level data from the Bitcoin exchange Mt.Gox,including over 1.4 million transactions from more than 45,000 traders,to investigate the role of technical chart patterns in the early Bitcoin market from...We use transaction-level data from the Bitcoin exchange Mt.Gox,including over 1.4 million transactions from more than 45,000 traders,to investigate the role of technical chart patterns in the early Bitcoin market from April 2011 to September 2013.Employing a pattern recognition algorithm,we identify hourly trading signals for five major chart patterns.Buy signals of these patterns are associated with an average increase in abnormal trading volume of more than 53%.Trades executed during buy signal periods yield significantly higher average returns than those made during non-signal periods.Traders who use chart patterns more frequently are more likely to generate right-skewed return distributions,engage in more active trading,and achieve higher average roundtrip returns.Our research suggests that chart pattern trading was a crucial tool for Mt.Gox clients,highlighting the importance of technical heuristics in shaping the dynamics in a less efficient and unregulated market environment.By leveraging a comprehensive transaction dataset from a major cryptocurrency exchange,we provide unique insights into the actual trading behavior of the first Bitcoin adopters.This sets our work apart from previous studies that mainly rely on backtesting technical strategies using publicly available price data.展开更多
Seed dispersal is a pivotal process in seed plant life cycle,owing to its effects on seed germination,seedling survival,population recruitment,and diversity maintenance in the entire community(Howe and Smallwood,1982;...Seed dispersal is a pivotal process in seed plant life cycle,owing to its effects on seed germination,seedling survival,population recruitment,and diversity maintenance in the entire community(Howe and Smallwood,1982;Rogers et al.,2021).There are diverse dispersal modes,such as anemochory(wind-driven dispersal),hydrochory(water-mediated dispersal),autochory(self-dispersal),and zoochory,which relies on a diverse array of animals for seed dispersal(Howe and Smallwood,1982).It is widely known that these varying dispersal modes impose selective pressures on many seed and fruit traits,especially the seed size,a key trait which is associated with multiple stages of the life cycle of plants,such as dispersal,germination,and establishment,particularly during early development(Leishman et al.,2000).展开更多
The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the an...The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the analysis of characteristic lines and crossover behaviors within the supercritical region.By making use of the free energy,we introduce three key thermodynamic quantities:scaled variance,skewness,and kurtosis.Our results demonstrate that the Widom line,associated with the maximal scaled variance,can effectively differentiate between small and large black hole-like subphases,each displaying distinct thermodynamic behaviors within the supercritical region.Furthermore,by utilizing quasinormal modes,we identify the Frenkel line,offering a dynamic perspective to distinguish between small and large black hole-like subphases.These contribute to a deeper comprehension of black hole subphases in the supercritical region,thus illuminating new facets of black hole thermodynamics.展开更多
Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate becau...Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.展开更多
文摘In this study,we propose a Gram-Charlier expansion approach to investigate the impact of skewness and kurtosis on production and hedging decisions.Consistent with the existing literature,we find that skewness and kurtosis do not affect decisions regarding optimal production;however,they significantly influence optimal hedging decisions.We observe that positive skewness with platykurtic spot prices or negative skewness with leptokurtic spot prices often leads to over-hedging when the initial forward contract price exceeds its expected value.Conversely,under-hedging is expected when the initial forward contract price falls below its expected value.In other conditions,skewness can either promote or impede speculative future trading.Using the Gram-Charlier expansion of the spot price density function,we find that optimal future positions depend on forward prices,the hedgers’risk preference,and the spot price distribution.Simulations validate our findings on the impact of skewness and kurtosis on future hedging.Finally,we analyze of a cotton storage and forward contracting dataset to illustrate the application of our methodology and support our theoretical results.
基金Supported by the National Basic Research Program of China (973 Program)(No 2007CB816005)the National Natural Science Foundation of China (No 40706003)+1 种基金International S&T Cooperation Project of the Ministry of Science and Technology of China (No2009DFA21430)the COPES in China (GYHY200706005)
文摘The skewness of subsurface temperature anomaly in the equatorial Pacific Ocean shows a significant asymmetry between the east and west. A positive temperature skewness appears in the equatorial eastern Pacific, while the temperature skewness in the western and central Pacific is primarily negative. There is also an asymmetry of the temperature skewness above and below the climatological mean therrnocline in the central and western Pacific. A positive skewness appears below the thermocline, but the skewness is negative above the thermocline. The distinctive vertical asymmetry of the temperature skewness is argued to be attributed to the asymmetric temperature response to upward and downward thermocline displacement in the presence of the observed upper-ocean vertical thermal structure. Because of positive （negative） second derivative of temperature with respect to depth below （above） the thermocline, an upward and a downward shift of the thermocline with equal displacement would lead to a negative temperature skewness above the thermocline but a positive skewness below the thermocline. In the far eastern equatorial Pacific, the thermocline is close to the base of the mixed layer, the shape of the upper-ocean vertical temperature profile cannot be kept. Positive skewness appears in both below the thermocline and above the thermocline in the far eastern basin. Over the central and eastern Pacific, the anomalies of the subsurface waters tend to entrain into the surface mixed layer （by climatological mean upwelling） and then affect the SST. Hence, the positive （negative） subsurface skewness in the far eastern （central） Pacific may favor positive （negative） SST skewness, which is consistent with the observational fact that more La Nina （EI Nino） occur in the central （eastern） Pacific. The present result implies a possible new paradigm for EI Nino and La Nina amplitude asymmetry in the eastern Pacific.
基金The project supported by the National Basic Research Program "Non-linear Science"
文摘Using nonequilibrium statistical mechanics closure method, it is shown that the skewness factor of the velocity derivative of isotropic turbulence ap- proaches a constant -0.515 when the Reynolds number is very high, which is in agree- ment with the DNS (direct numerical simulation) result of Vincent and Meneguzzi (1991).
基金Supported by the National Natural Science Foundation of China(11261025,11561075)the Natural Science Foundation of Yunnan Province(2016FB005)the Program for Middle-aged Backbone Teacher,Yunnan University
文摘Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this paper, we propose and study a novel class of models： a skew-normal mixture of joint location, scale and skewness models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The issues of maximum likelihood estimation are addressed. In particular, an Expectation-Maximization （EM） algorithm for estimating the model parameters is developed. Properties of the estimators of the regression coefficients are evaluated through Monte Carlo experiments. Results from the analysis of a real data set from the Body Mass Index （BMI） data are presented.
文摘In this study, the statistical powers of Kolmogorov-Smimov two-sample （KS-2） and Wald Wolfowitz （WW） tests, non-parametric tests used in testing data from two independent samples, have been compared in terms of fixed skewness and fixed kurtosis by means of Monte Carlo simulation. This comparison has been made when the ratio of variance is two as well as with equal and different sample sizes for large sample volumes. The sample used in the study is： （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 25）, （50, 50）, （50, 75）, （50, 100）, （75, 25）, （75, 50）, （75, 75）, （75, 100）, （100, 25）, （100, 50）, （100, 75）, and （100, 100）. According to the results of the study, it has been observed that the statistical power of both tests decreases when the coefficient of kurtosis is held fixed and the coefficient of skewness is reduced while it increases when the coefficient of skewness is held fixed and the coefficient of kurtosis is reduced. When the ratio of skewness is reduced in the case of fixed kurtosis, the WW test is stronger in sample volumes （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 75）, and （50, 100） while KS-2 test is stronger in other sample volumes. When the ratio of kurtosis is reduced in the case of fixed skewness, the statistical power of WW test is stronger in volume samples （25, 25）, （25, 75）, （25, 100）, and （75, 25） while KS-2 test is stronger in other sample volumes.
基金Project supported by the National Natural Science Foundation of China(Grant No.11772032)the Science Foundation of North University of China(Grant No.11026829).
文摘The turbulence governed by the Navier-Stokes equation is paramount in many physical processes.However,it has been considered as a challenging problem due to its inherent nonlinearity,non-equilibrium,and complexity.Herein,we review the connections between the velocity derivative skewness Sk and the non-equilibrium properties of turbulence.Sk,a reasonable candidate for describing the non-equilibrium turbulence,which varies during the non-equilibrium procedure.A lot of experimental or numerical evidences have shown that the perturbation of energy spectrum,which associated with the excitation of large scales,results in an obvious variation of Sk,and Sk is a negative value in this rapid energy decay process.The variation of positive Sk is closely related to the perturbation of transfer spectrum,and this corresponds to the backward energy transfer process.In addition,the skewness characterizes the production(or reduction)rate of enstrophy due to vortex stretching(or compression).Using the transport equation of turbulent energy dissipation rate and enstrophy,it is possible to establish a theoretical connection between skewness and the non-equilibrium turbulence.It is expected that this work could trigger the rapid advancement of the future studies of non-equilibrium turbulence,and also the improvement of turbulence models.
基金supported by the National Natural Science Foundation of China(Grant Nos.12202187,92266201 and 92266301)the Fundamental Research Funds for the Central Universities(Grant No.30924010819).
文摘Non-Gaussian random vibrations have gained more attention in the dynamics-research community due to the frequently encountered non-Gaussian dynamic environments in engineering practice.This work proposes a novel non-Gaussian random vibration test method by simultaneous control of multiple correlation coefficients,skewness,and kurtoses.The multi-channel time-domain coupling model is first constructed which is mainly composed of the designed parameters and independent signal sources.The designed parameters are related to the defined correlation coefficients and root mean square values.The synthesized multiple non-Gaussian random signals are unitized to provide independent signal sources for coupling.The first four statistical characteristics of the synthesized non-Gaussian random signals are theoretically derived so that the relationships among the generated signals,independent signal sources,and correlation coefficients are achieved.Subsequently,a multi-channel closed-loop equalization procedure for non-Gaussian random vibration control is presented to produce a multi-channel correlated non-Gaussian random vibration environment.Finally,a simulation example and an experimental verification are provided.Results from the simulation and experiment indicate that the multi-channel response spectral densities,correlation coefficients,skewnesses,and kurtoses can be stably and effectively controlled within the corresponding tolerances by the proposed method.
文摘Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice. One reason for this may be the lack of dissemination and further exploration of this new measure. Additionally, the authors focused mainly on specific probability distributions. One of the advantages of AS is that it considers the entire shape of the distribution, rather than focusing only on moments or the linear distance between central tendency statistics or quantiles. This holistic approach makes AS particularly robust in cases where the distribution deviates from normality or contains outliers. This paper aims to generalize its use to random samples with either known or unknown distributions. The study has three objectives: 1) to develop an R script for point and interval estimation of AS;2) to provide interpretive norms of normality by examining normality in bootstrap sampling distributions;and 3) to compare asymptotic and bootstrap standard errors. Interval estimation is approached asymptotically and through bootstrap. The script was illustrated using two examples: one with generated data and another with real-world data. Interpretive norms of normality are derived from 40 samples of various sizes, created by inverse transform sampling to follow a standard normal distribution. Bootstrap intervals at three confidence levels (0.9, 0.95, and 0.99) were obtained using the normal method, with two exceptions: the bias-corrected and accelerated percentile method for the 60-data sample and the percentile method for the 600-data sample, as these deviated from normality. Asymptotic 95% confidence intervals are also provided. The asymptotic standard error was larger than the bootstrap one, with the difference decreasing as the sample size increased. The script is concluded to have practical and educational utility for estimating AS, whose asymptotic sampling distribution is normal.
基金supported by China Natural Science Foundation (70701035, 70425004 and 70221001)Hunan Natural Science Foundation (09JJ1010)+1 种基金the Key Research Institute of PhilosophiesSocial Sciences in Hunan Universities
文摘The skewness of the return distribution is one of the important features of the security price.In this paper,the authors try to explore the relationship between the skewness and the coefficient ofrisk premium.The coefficient of the risk premium is estimated by a GARCH-M model,and the robustmeasurement of skewness is calculated by Groeneveld-Meeden method.The empirical evidences forthe composite indexes from 33 securities markets in the world indicate that the risk compensationrequirement in the market where the return distribution is positively skewed is virtually zero,andthe risk compensation requirement is positive in a significant level in the market where the returndistribution is negative skewed.Moreover,the skewness is negatively correlated with the coefficient ofthe risk premium.
基金supported by the National Natural Science Foundation of China under Grant Nos.11261025,11561075the Natural Science Foundation of Yunnan Province under Grant No.2016FB005the Program for Middle-aged Backbone Teacher,Yunnan University
文摘Variable selection is an important research topic in modern statistics, traditional variable selection methods can only select the mean model and(or) the variance model, and cannot be used to select the joint mean, variance and skewness models. In this paper, the authors propose the joint location, scale and skewness models when the data set under consideration involves asymmetric outcomes,and consider the problem of variable selection for our proposed models. Based on an efficient unified penalized likelihood method, the consistency and the oracle property of the penalized estimators are established. The authors develop the variable selection procedure for the proposed joint models, which can efficiently simultaneously estimate and select important variables in location model, scale model and skewness model. Simulation studies and body mass index data analysis are presented to illustrate the proposed methods.
文摘The skewness of a graph G is the minimum number of edges in G whose removal results in a planar graph. In this paper, we determine the skewness of the generalized Petersen graph P（4k, k） and hence a lower bound for the crossing number of P（4k, k）. In addition, an upper bound for the crossing number of P（4k, k） is also given.
基金supported by the National Natural Science Foundation of China under Grant Nos.61972025,61802389,61672092,U1811264,and 61966009the National Key Research and Development Program of China under Grant Nos.2020YFB1005604 and 2020YFB2103802Guangxi Key Laboratory of Trusted Software under Grant No.KX201902.
文摘Reinforcement learning as autonomous learning is greatly driving artificial intelligence(AI)development to practical applications.Having demonstrated the potential to significantly improve synchronously parallel learning,the parallel computing based asynchronous advantage actor-critic(A3C)opens a new door for reinforcement learning.Unfortunately,the acceleration's influence on A3C robustness has been largely overlooked.In this paper,we perform the first robustness assessment of A3C based on parallel computing.By perceiving the policy's action,we construct a global matrix of action probability deviation and define two novel measures of skewness and sparseness to form an integral robustness measure.Based on such static assessment,we then develop a dynamic robustness assessing algorithm through situational whole-space state sampling of changing episodes.Extensive experiments with different combinations of agent number and learning rate are implemented on an A3C-based pathfinding application,demonstrating that our proposed robustness assessment can effectively measure the robustness of A3C,which can achieve an accuracy of 83.3%.
基金the National Natural Science Foundation of China(No.72203249)Peng acknowledges financial support from the National Natural Science Foundation of China(No.71903208,72273160).
文摘Under probability weighting,entrepreneurs with skewness preference tend to seek rightskewed and avoid left-skewed risks.We show that Chinese firms managed by CEOs with professional epidemic experience,i.e.,who previously experienced the outbreak of SARS during their tenure as high level executives,have a lower stock price crash risk measured by the negative skewness of stock prices in subsequent periods.In particular,those firms intentionally avoid stock price crashes by adopting more conservative strategies in decisionmaking.Overall,we provide the first evidence on the unintended effect of entrepreneurs'subjective judgments of the probabilities of disease outbreaks on financial market stability.These have long-term implications for the financial system.
文摘In this paper, we propose a new approach to the test of elliptical symmetry based on theprojection pursuit (P.P.) technique, the number-theoretic method, skewness and kurtosis. Thelimiting null distributions of the new statistics are derived. The powers of the tests against sixalternatives are calculated by simulation, which shows that the new t.st's are acceptable.
文摘We use transaction-level data from the Bitcoin exchange Mt.Gox,including over 1.4 million transactions from more than 45,000 traders,to investigate the role of technical chart patterns in the early Bitcoin market from April 2011 to September 2013.Employing a pattern recognition algorithm,we identify hourly trading signals for five major chart patterns.Buy signals of these patterns are associated with an average increase in abnormal trading volume of more than 53%.Trades executed during buy signal periods yield significantly higher average returns than those made during non-signal periods.Traders who use chart patterns more frequently are more likely to generate right-skewed return distributions,engage in more active trading,and achieve higher average roundtrip returns.Our research suggests that chart pattern trading was a crucial tool for Mt.Gox clients,highlighting the importance of technical heuristics in shaping the dynamics in a less efficient and unregulated market environment.By leveraging a comprehensive transaction dataset from a major cryptocurrency exchange,we provide unique insights into the actual trading behavior of the first Bitcoin adopters.This sets our work apart from previous studies that mainly rely on backtesting technical strategies using publicly available price data.
基金funded by National Natural Science Foundation of China(32171533 and 31971444)Anhui Provincial Natural Science Foundation(2208085J28).
文摘Seed dispersal is a pivotal process in seed plant life cycle,owing to its effects on seed germination,seedling survival,population recruitment,and diversity maintenance in the entire community(Howe and Smallwood,1982;Rogers et al.,2021).There are diverse dispersal modes,such as anemochory(wind-driven dispersal),hydrochory(water-mediated dispersal),autochory(self-dispersal),and zoochory,which relies on a diverse array of animals for seed dispersal(Howe and Smallwood,1982).It is widely known that these varying dispersal modes impose selective pressures on many seed and fruit traits,especially the seed size,a key trait which is associated with multiple stages of the life cycle of plants,such as dispersal,germination,and establishment,particularly during early development(Leishman et al.,2000).
基金supported by the National Natural Science Foundation of China(Grant Nos.12473001,11975072,11875102,11835009,and 11965013)the National SKA Program of China(Grant Nos.2022SKA0110200 and 2022SKA0110203)+1 种基金the National 111 Project(Grant No.B16009)supported by Yunnan High-level Talent Training Support Plan Young&Elite Talents Project(Grant No.YNWR-QNBJ-2018-181).
文摘The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the analysis of characteristic lines and crossover behaviors within the supercritical region.By making use of the free energy,we introduce three key thermodynamic quantities:scaled variance,skewness,and kurtosis.Our results demonstrate that the Widom line,associated with the maximal scaled variance,can effectively differentiate between small and large black hole-like subphases,each displaying distinct thermodynamic behaviors within the supercritical region.Furthermore,by utilizing quasinormal modes,we identify the Frenkel line,offering a dynamic perspective to distinguish between small and large black hole-like subphases.These contribute to a deeper comprehension of black hole subphases in the supercritical region,thus illuminating new facets of black hole thermodynamics.
文摘Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.
