In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance c...In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.展开更多
Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,t...Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,the site-to-fault distance and the site foundation properties.In the present study,the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an effi ciency-robustness balanced formula is proposed.For this purpose,a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship.In this approach,each model class(a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data.The one with the highest plausibility is robust since it possesses the optimal balance between the data fi tting capability and the sensitivity to noise.A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis.The optimal predictive formula is proposed based on this database.It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore,Joyner and Fumal(1993).展开更多
Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that t...Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.展开更多
Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas ...Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.展开更多
The solution of the grey model(GM(1,1)model)generally involves equal-precision observations,and the(co)variance matrix is established from the prior information.However,the data are generally available with unequal-pr...The solution of the grey model(GM(1,1)model)generally involves equal-precision observations,and the(co)variance matrix is established from the prior information.However,the data are generally available with unequal-precision measurements in reality.To deal with the errors of all observations for GM(1,1)model with errors-in-variables(EIV)structure,we exploit the total least-squares(TLS)algorithm to estimate the parameters of GM(1,1)model in this paper.Ignoring that the effect of the improper prior stochastic model and the homologous observations may degrade the accuracy of parameter estimation,we further present a nonlinear total least-squares variance component estimation approach for GM(1,1)model,which resorts to the minimum norm quadratic unbiased estimation(MINQUE).The practical and simulative experiments indicate that the presented approach has significant merits in improving the predictive accuracy in comparison with control methods.展开更多
In this paper, we focus on a constant elasticity of variance （CEV） modeland want to find its optimal strategies for a mean-variance problem under two constrainedcontrols： reinsurance/new business and investment （n...In this paper, we focus on a constant elasticity of variance （CEV） modeland want to find its optimal strategies for a mean-variance problem under two constrainedcontrols： reinsurance/new business and investment （no-shorting）. First, aLagrange multiplier is introduced to simplify the mean-variance problem and thecorresponding Hamilton-Jacobi-Bellman （HJB） equation is established. Via a powertransformation technique and variable change method, the optimal strategies withthe Lagrange multiplier are obtained. Final, based on the Lagrange duality theorem,the optimal strategies and optimal value for the original problem （i.e., the efficientstrategies and efficient frontier） are derived explicitly.展开更多
In this paper,we consider the estimates d of error variance d2=Var(ei) in the linear models Yi=x' iβ+ei(i= 1, 2, ... ). We study the complete convergence of dm2-o2 when the error {ei }is a sequence of identically...In this paper,we consider the estimates d of error variance d2=Var(ei) in the linear models Yi=x' iβ+ei(i= 1, 2, ... ). We study the complete convergence of dm2-o2 when the error {ei }is a sequence of identically distributed p-mixing variables. And we also obtain the better convergence rates when {ei} is not identically distribution展开更多
The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is...The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is to present a test of heteroscedasticity for nonlinear semiparametric regression models with nonparametric variance function. The validity of the proposed test is illustrated by two simulated examples and a real data example.展开更多
This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficient...This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficients of the parameter part of the Varying Index Coefficient Model (VICM), while the unknown function part uses the B-spline to expand. Moreover, we combine the above two estimation methods under the assumption of high-dimensional data. The results of data simulation and empirical analysis show that for the varying index coefficient model, the re-adjusted cross-validation method is better in terms of accuracy and stability than traditional methods based on ordinary least squares.展开更多
Assuming the investor is uncertainty-aversion,the multiprior approach is applied to studying the problem of portfolio choice under the uncertainty about the expected return of risky asset based on the mean-variance mo...Assuming the investor is uncertainty-aversion,the multiprior approach is applied to studying the problem of portfolio choice under the uncertainty about the expected return of risky asset based on the mean-variance model. By introducing a set of constraint constants to measure uncertainty degree of the estimated expected return,it built the max-min model of multi-prior portfolio,and utilized the Lagrange method to obtain the closed-form solution of the model,which was compared with the mean-variance model and the minimum-variance model; then,an empirical study was done based on the monthly returns over the period June 2011 to May 2014 of eight kinds of stocks in Shanghai Exchange 50 Index. Results showed,the weight of multi-prior portfolio was a weighted average of the weight of mean-variance portfolio and that of minimumvariance portfolio; the steady of multi-prior portfolio was strengthened compared with the mean-variance portfolio; the performance of multi-prior portfolio was greater than that of minimum-variance portfolio. The study demonstrates that the investor can improve the steady of multi-prior portfolio as well as its performance for some appropriate constraint constants.展开更多
Most left ventricular(LV)Doppler measurements vary significantly with age and gender,making it necessary to correct them for physiological variances.We aimed to verify the hypothesis that different Doppler measurement...Most left ventricular(LV)Doppler measurements vary significantly with age and gender,making it necessary to correct them for physiological variances.We aimed to verify the hypothesis that different Doppler measurements correlate nonlinearly with different biometric variables raised to different scaling factors and exponents.In this work,a total of 23 LV Doppler parameters were measured in 1224 healthy Chinese adults.An optimized multivariable allometric model(OMAM)and scaling equations were developed in 70%of the subjects(group A),and the reliability of the model and equations was verified using the remaining 30%of the subjects(group B)as well as 183 overweight subjects(group C).The single-variable isometric model(SVIM)with body surface area(BSA)as a scaling variable was used for comparison.Before correction,all 23 LV Doppler parameters correlated significantly with one or more of the biometric variables.In group B,gender differences were found in 47.8%(11/23)of the parameters and were eliminated in 81.8%(9/11)of the parameters after correction with OMAM.The successful correction rate with OMAM was 100%(23/23)in group B and 82.6%(19/23)in group C.New reference values for corrected Doppler measurements independent of biometric variables were established.The SVIM with BSA successfully corrected none of the 23 parameters.In conclusion,different LV Doppler parameters allometrically correlated with one or more of the biometric variables.The novel OMAM developed in this study successfully corrected the effects of the physiological variances of most biometric variables on Doppler measurements in healthy and overweight subjects,and was found to be far superior to the SVIM.However,whether the OMAM equations can be applied to other ethnicities,obese subjects,and pathological conditions requires further investigation.展开更多
Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are ...Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.展开更多
This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physic...This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physical form.The trade of gold futures relates to seasons,festivity,and government policy.So,the paper will discuss seasonality and intervention in the analysis.Due to non-constant variance,we will also use the standard variance stabilization transformation method and the ARIMA/GARCH modelling method to compare the forecast performance on the gold futures prices.The results from the analysis show that while the standard variance transformation method may provide better point forecast values,the ARIMA/GARCH modelling method provides much shorter forecast intervals.The empirical results of this study which rationalise the effect of seasonality in the Indian bullion derivative market have not been reported in literature.展开更多
Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon a...Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon and solve the ‘volatility smile dilemma’.This paper combines the variance gamma model with the least squares Monte Carlo simulation method to empirically analyze the Everbright convertible bond based on its high activity in the Chinese market.In this paper,the predicted price and the actual price are compared,and the applicability of the variance gamma model in the Chinese convertible bond market is analyzed.Empirical results show that the fitting price predicted by the variance gamma model is consistent with the actual price trend,indicating that the method is applicable to the Chinese convertible bond market.展开更多
An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances ...An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...展开更多
基金supported by the National Natural Science Foundation of China(No.42174011)。
文摘In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.
基金Research Committee of University of Macao under Research Grant No.MYRG081(Y1-L2)-FST13-YKVthe Science and Technology Development Fund of the Macao SAR government under Grant No.012/2013/A1
文摘Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,the site-to-fault distance and the site foundation properties.In the present study,the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an effi ciency-robustness balanced formula is proposed.For this purpose,a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship.In this approach,each model class(a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data.The one with the highest plausibility is robust since it possesses the optimal balance between the data fi tting capability and the sensitivity to noise.A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis.The optimal predictive formula is proposed based on this database.It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore,Joyner and Fumal(1993).
基金The project is partly supported by NSFC (19971085)the Doctoral Program Foundation of the Institute of High Education and the Special Foundation of Chinese Academy of Sciences.
文摘Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.
基金CRC MiningThe University of Queensland for their financial support for this study
文摘Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.
基金supported by the National Natural Science Foundation of China(No.41874001 and No.41664001)Support Program for Outstanding Youth Talents in Jiangxi Province(No.20162BCB23050)National Key Research and Development Program(No.2016YFB0501405)。
文摘The solution of the grey model(GM(1,1)model)generally involves equal-precision observations,and the(co)variance matrix is established from the prior information.However,the data are generally available with unequal-precision measurements in reality.To deal with the errors of all observations for GM(1,1)model with errors-in-variables(EIV)structure,we exploit the total least-squares(TLS)algorithm to estimate the parameters of GM(1,1)model in this paper.Ignoring that the effect of the improper prior stochastic model and the homologous observations may degrade the accuracy of parameter estimation,we further present a nonlinear total least-squares variance component estimation approach for GM(1,1)model,which resorts to the minimum norm quadratic unbiased estimation(MINQUE).The practical and simulative experiments indicate that the presented approach has significant merits in improving the predictive accuracy in comparison with control methods.
基金The NSF(11201111) of ChinaHebei Province Colleges and Universities Science,and Technology Research Project(ZD20131017)
文摘In this paper, we focus on a constant elasticity of variance （CEV） modeland want to find its optimal strategies for a mean-variance problem under two constrainedcontrols： reinsurance/new business and investment （no-shorting）. First, aLagrange multiplier is introduced to simplify the mean-variance problem and thecorresponding Hamilton-Jacobi-Bellman （HJB） equation is established. Via a powertransformation technique and variable change method, the optimal strategies withthe Lagrange multiplier are obtained. Final, based on the Lagrange duality theorem,the optimal strategies and optimal value for the original problem （i.e., the efficientstrategies and efficient frontier） are derived explicitly.
文摘In this paper,we consider the estimates d of error variance d2=Var(ei) in the linear models Yi=x' iβ+ei(i= 1, 2, ... ). We study the complete convergence of dm2-o2 when the error {ei }is a sequence of identically distributed p-mixing variables. And we also obtain the better convergence rates when {ei} is not identically distribution
基金Supported by the Natural Science Foundation of Jiangsu Province (BK2008284)
文摘The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is to present a test of heteroscedasticity for nonlinear semiparametric regression models with nonparametric variance function. The validity of the proposed test is illustrated by two simulated examples and a real data example.
文摘This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficients of the parameter part of the Varying Index Coefficient Model (VICM), while the unknown function part uses the B-spline to expand. Moreover, we combine the above two estimation methods under the assumption of high-dimensional data. The results of data simulation and empirical analysis show that for the varying index coefficient model, the re-adjusted cross-validation method is better in terms of accuracy and stability than traditional methods based on ordinary least squares.
基金National Natural Science Foundations of China(Nos.71271003,71171003)Programming Fund Project of the Humanities and Social Sciences Research of the Ministry of Education of China(No.12YJA790041)
文摘Assuming the investor is uncertainty-aversion,the multiprior approach is applied to studying the problem of portfolio choice under the uncertainty about the expected return of risky asset based on the mean-variance model. By introducing a set of constraint constants to measure uncertainty degree of the estimated expected return,it built the max-min model of multi-prior portfolio,and utilized the Lagrange method to obtain the closed-form solution of the model,which was compared with the mean-variance model and the minimum-variance model; then,an empirical study was done based on the monthly returns over the period June 2011 to May 2014 of eight kinds of stocks in Shanghai Exchange 50 Index. Results showed,the weight of multi-prior portfolio was a weighted average of the weight of mean-variance portfolio and that of minimumvariance portfolio; the steady of multi-prior portfolio was strengthened compared with the mean-variance portfolio; the performance of multi-prior portfolio was greater than that of minimum-variance portfolio. The study demonstrates that the investor can improve the steady of multi-prior portfolio as well as its performance for some appropriate constraint constants.
基金supported by the Program of Introducing Talents of Discipline to Universities(BP 0719033)the State Key Program of the National Natural Science Foundation of China(82030051)+4 种基金the International Collaboration and Exchange Program of China(81920108003)the National Natural Science Foundation of China(81671703,81770442,and 11771408)the Qingdao Key Health Discipline Development Fund(3311000000073)the People’s Livelihood Science and Technology Project of Qingdao(18-6-1-62-nsh)the Fundamental Research Funds for the Central Universities(201964006)。
文摘Most left ventricular(LV)Doppler measurements vary significantly with age and gender,making it necessary to correct them for physiological variances.We aimed to verify the hypothesis that different Doppler measurements correlate nonlinearly with different biometric variables raised to different scaling factors and exponents.In this work,a total of 23 LV Doppler parameters were measured in 1224 healthy Chinese adults.An optimized multivariable allometric model(OMAM)and scaling equations were developed in 70%of the subjects(group A),and the reliability of the model and equations was verified using the remaining 30%of the subjects(group B)as well as 183 overweight subjects(group C).The single-variable isometric model(SVIM)with body surface area(BSA)as a scaling variable was used for comparison.Before correction,all 23 LV Doppler parameters correlated significantly with one or more of the biometric variables.In group B,gender differences were found in 47.8%(11/23)of the parameters and were eliminated in 81.8%(9/11)of the parameters after correction with OMAM.The successful correction rate with OMAM was 100%(23/23)in group B and 82.6%(19/23)in group C.New reference values for corrected Doppler measurements independent of biometric variables were established.The SVIM with BSA successfully corrected none of the 23 parameters.In conclusion,different LV Doppler parameters allometrically correlated with one or more of the biometric variables.The novel OMAM developed in this study successfully corrected the effects of the physiological variances of most biometric variables on Doppler measurements in healthy and overweight subjects,and was found to be far superior to the SVIM.However,whether the OMAM equations can be applied to other ethnicities,obese subjects,and pathological conditions requires further investigation.
基金Supported by the National Natural Science Foundation of China（60375003） Supported by the Chinese Aviation Foundation（03153059）
文摘Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.
基金supported by the Fulbright-Nehru Doctoral Research program(Award No.2447/DR/2019-2020).
文摘This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physical form.The trade of gold futures relates to seasons,festivity,and government policy.So,the paper will discuss seasonality and intervention in the analysis.Due to non-constant variance,we will also use the standard variance stabilization transformation method and the ARIMA/GARCH modelling method to compare the forecast performance on the gold futures prices.The results from the analysis show that while the standard variance transformation method may provide better point forecast values,the ARIMA/GARCH modelling method provides much shorter forecast intervals.The empirical results of this study which rationalise the effect of seasonality in the Indian bullion derivative market have not been reported in literature.
文摘Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon and solve the ‘volatility smile dilemma’.This paper combines the variance gamma model with the least squares Monte Carlo simulation method to empirically analyze the Everbright convertible bond based on its high activity in the Chinese market.In this paper,the predicted price and the actual price are compared,and the applicability of the variance gamma model in the Chinese convertible bond market is analyzed.Empirical results show that the fitting price predicted by the variance gamma model is consistent with the actual price trend,indicating that the method is applicable to the Chinese convertible bond market.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDA20060500]the National Natural Science Foundation of China[grant numbers 41731173 and 42275035]+8 种基金the Natural Science Foundation of Guangdong ProvinceChina [grant number 2022A1515011967]the Science and Technology Program of GuangzhouChina [grant number 202002030492]the Open Fund Project of the Key Laboratory of Marine Environmental Information Technology,the Key Laboratory of Marine Science and Numerical Modeling,Ministry of Natural Resources of the People’s Republic of China [grant number 2020-YB-05]the MEL Visiting Fellowship [grant number MELRS2102]the Independent Research Project Program of the State Key Laboratory of Tropical Oceanography [grant number LTOZZ2005]the Key Special Project for the Introducing Talents Team of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)[grant number GML2019ZD0306]the Innovation Academy of South China Sea Ecology and Environmental Engineering [grant number ISEE2018PY06]
基金National Basic Research Program of China (JW132006093)
文摘An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...
