WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted ma...WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http：//agbu. une.edu.au/-kmeyer/wombat.html展开更多
In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more...In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorre, lated or even negatively correlated contingencies. This raises important issues of cooperation and risk sharing among diverse producers. For large-scale practical allocation problems when information on the contingencies may be disperse, not analytically tractable, or be available on aggregate levels, we propose a downscaling procedure based on behavioral principles utilizing spatial risk preference structure, It allows for estimation of production allocation at required resolutions accounting for location specific risks and suitability constraints. The approach provides a tool for harmonization of data from various spatial levels. We applied the method in a case study of livestock production allocation in China to 2030.展开更多
Accelerated degradation test is a useful approach to predict the product lifetime at the normal use stress level, especially for highly reliable products. Two kinds of the lifetime prediction based on Gamma processes ...Accelerated degradation test is a useful approach to predict the product lifetime at the normal use stress level, especially for highly reliable products. Two kinds of the lifetime prediction based on Gamma processes were studied. One was to predict the lifetime of the population from accelerated degradation data, and the other was to predict the lifetime of an individual by taking the accelerated degradation data as prior information. For an extensive application, the Gamma process with a time transformation and random effects was considered. A novel contribution is that a deducing method for determining the relationships between the shape and scale parameters of Gamma processes and accelerated stresses was presented. When predicting the lifetime of an individual, Bayesian inference methods were adopted to improve the prediction accuracy, in which the conjugate prior distribution and the non-conjugate prior distribution of random parameters were studied. The conjugate prior distribution only considers the random effect of the scale parameter while the non-conjugate prior distribution considers the random effects of both the scale and shape parameter. The application and usefulness of the proposed method was demonstrated by the accelerated degradation data of carbon-film resistors.展开更多
Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degrad...Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.展开更多
In this paper, we have discussed a random censoring test with incomplete information, and proved that the maximum likelihood estimator(MLE) of the parameter based on the randomly censored data with incomplete informat...In this paper, we have discussed a random censoring test with incomplete information, and proved that the maximum likelihood estimator(MLE) of the parameter based on the randomly censored data with incomplete information in the case of the exponential distribution has the strong consistency.展开更多
Maximum Likelihood （ML） method has an excellent performance for Direction-Of-Arrival （DOA） estimation, but a mul- tidimensional nonlinear solution search is required which complicates the computation and prevents ...Maximum Likelihood （ML） method has an excellent performance for Direction-Of-Arrival （DOA） estimation, but a mul- tidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony （ABC） algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the be- havior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the con- ventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio （SNR）, and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investi- gated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.展开更多
This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the...This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the sample. It is shown that the adaptive estimator defined in this paper is asymptotically most efficient in the sense that it is asymptotic normal, and the covariance matrix of the limit distribution coincides with the one for the quasi-likelihood estimator for the case that the covariance matrix of the response variable is completely known.展开更多
In this paper, a partially linear single-index model is investigated, and three empirical log-likelihood ratio statistics for the unknown parameters in the model are suggested. It is proved that the proposed statistic...In this paper, a partially linear single-index model is investigated, and three empirical log-likelihood ratio statistics for the unknown parameters in the model are suggested. It is proved that the proposed statistics are asymptotically standard chi-square under some suitable conditions, and hence can be used to construct the confidence regions of the parameters. Our methods can also deal with the confidence region construction for the index in the pure single-index model. A simulation study indicates that, in terms of coverage probabilities and average areas of the confidence regions, the proposed methods perform better than the least-squares method.展开更多
In this paper, we consider the semiparametric regression model for longitudinal data. Due to the correlation within groups, a generalized empirical log-likelihood ratio statistic for the unknown parameters in the mode...In this paper, we consider the semiparametric regression model for longitudinal data. Due to the correlation within groups, a generalized empirical log-likelihood ratio statistic for the unknown parameters in the model is suggested by introducing the working covariance matrix. It is proved that the proposed statistic is asymptotically standard chi-squared under some suitable conditions, and hence it can be used to construct the confidence regions of the parameters. A simulation study is conducted to compare the proposed method with the generalized least squares method in terms of coverage accuracy and average lengths of the confidence intervals.展开更多
This article provides a brief overview of various approaches that may be utilized for the analysis of human semen test results. Reference intervals are the most widely used tool for the interpretation of clinical labo...This article provides a brief overview of various approaches that may be utilized for the analysis of human semen test results. Reference intervals are the most widely used tool for the interpretation of clinical laboratory results. Reference interval development has classically relied on concepts elaborated by the International Federation of Clinical Chemistry Expert Panel on Reference Values during the 1980s. These guidelines involve obtaining and classifying samples from a healthy population of at least 120 individuals and then identifying the outermost 5% of observations to use in defining limits for two-sided or one-sided reference intervals. More recently, decision limits based on epidemiological outcome analysis have also been introduced to aid in test interpretation. The reference population must be carefully defined on the basis of the intended clinical use of the underlying test. To determine appropriate reference intervals for use in male fertility assessment, a reference population of men with documented time to pregnancy of 〈 12 months would be most suitable. However, for epidemiological assessment of semen testing results, a reference population made up ofunselected healthy men would be preferred. Although reference and decision limits derived for individual semen analysis test results will undoubtedly be the interpretational tools of choice in the near future, in the long term, multivariate methods for the interpretation of semen analysis alone or in combination with information from the female partner seem to represent better means for assessing the likelihood of achieving a successful pregnancy in a subfertile couple.展开更多
The limit properties of the dependent sequence of absolutely continuous random variables are investigated by using the notion of likelihood ratio, and a class of strong limit theorems, represented by inequalities, i.e...The limit properties of the dependent sequence of absolutely continuous random variables are investigated by using the notion of likelihood ratio, and a class of strong limit theorems, represented by inequalities, i.e. the strong deviation theorems, are obtained. In the proof an approach of applying the Laplace transformation to the investigation of the strong limit theorems is proposed.展开更多
As an extension of partially linear models and additive models, partially linear additive model is useful in statistical modelling. This paper proposes an empirical likelihood based approach for testing serial correla...As an extension of partially linear models and additive models, partially linear additive model is useful in statistical modelling. This paper proposes an empirical likelihood based approach for testing serial correlation in this semiparametric model. The proposed test method can test not only zero first-order serial correlation, but also higher-order serial correlation. Under the null hypothesis of no serial correlation, the test statistic is shown to follow asymptotically a chi-square distribution. Furthermore, a simulation study is conducted to illustrate the performance of the proposed method.展开更多
This paper studies a maximum likelihood estimator(MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling(RSS). The authors first find the optimal RSS according to the charact...This paper studies a maximum likelihood estimator(MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling(RSS). The authors first find the optimal RSS according to the character of the family, viz, arrange the RSS based on quasi complete and sufficient statistic of independent and identically distributed(iid) samples. Then under this RSS, some sufficient conditions for the existence and uniqueness of the MLE, which are easily used in practice,are obtained. Using these conditions, the existence and uniqueness of the MLEs of the parameters for some usual distributions in this family are proved. Numerical simulations for these distributions fully support the result from the above two step optimizations of the sampling and the estimation method.展开更多
Objective To determine the best statistical distribution of concentration data of major air pollutants in Shanghai. Methods Four types of theoretic distributions (lognormal, gamma, Pearson V and extreme value) were...Objective To determine the best statistical distribution of concentration data of major air pollutants in Shanghai. Methods Four types of theoretic distributions (lognormal, gamma, Pearson V and extreme value) were chosen to fit daily average concentration data of PM10, SO2 and NO2 from June 1, 2000 to May 31, 2003 in Shanghai by using the maximum likelihood method. The fit results were evaluated by Chi-square test. Results The best-fit distributions for PM10,SO2 and NO2 concentrations in Shanghai were lognormal, Pearson V, and extreme value distributions, respectively. Conclusion The results can be further applied to local air pollution prediction and control, e.g., the probabilities exceeding the air quality standard and emission source reduction of air pollutant concentration to meet the standard.展开更多
The method has been developed to accurately identify the magnitude of health risks and provide scientific evidence for implementation of risk management in food safety.It combines two parameters including consequence ...The method has been developed to accurately identify the magnitude of health risks and provide scientific evidence for implementation of risk management in food safety.It combines two parameters including consequence and likelihood of adverse effects based on risk matrix.Score definitions and classification for the consequence and the likelihood of adverse effects are proposed.The risk score identifies the intersection of consequence and likelihood in risk matrix represents its health risk level with different colors：‘low＇,‘medium＇,‘high＇.Its use in an actual case is shown.展开更多
: Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an ev...: Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an evergreen mixed forest in the Dinghushan Biosphere Reserve, South China. Plants in the tree, shrub and herb layers in 25 quadrats of 20 m× 20 m, 5 m× 5 m, and 1 m× 1 m were surveyed. Results indicated that: (i) for each layer, the observed species abundance with a similarly small median, mode, and a variance larger than the mean was reverse J-shaped and followed well the zero-truncated Poisson lognormal; (ii) the coefficient of variation, skewness and kurtosis of abundance, and two Poisson lognormal parameters (& and μ) for shrub layer were closer to those for the herb layer than those for the tree layer; and (iii) from the tree to the shrub to the herb layer, the α and the coefficient of variation decreased, whereas diversity increased. We suggest that: (i) the species abundance distributions in the three layers reflects the overall community characteristics; (ii) the Poisson lognormal can describe the species abundance distribution in diverse communities with a few abundant species but many rare species; and (iii) 1/α should be an alternative measure of diversity.展开更多
To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. ...To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).展开更多
基金Project (No. BFGEN.100B) supported by the Meat and LivestockLtd., Australia (MLA)
文摘WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http：//agbu. une.edu.au/-kmeyer/wombat.html
文摘In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorre, lated or even negatively correlated contingencies. This raises important issues of cooperation and risk sharing among diverse producers. For large-scale practical allocation problems when information on the contingencies may be disperse, not analytically tractable, or be available on aggregate levels, we propose a downscaling procedure based on behavioral principles utilizing spatial risk preference structure, It allows for estimation of production allocation at required resolutions accounting for location specific risks and suitability constraints. The approach provides a tool for harmonization of data from various spatial levels. We applied the method in a case study of livestock production allocation in China to 2030.
基金supported by the National Natural Science Foundation of China(No.61273058)
文摘Accelerated degradation test is a useful approach to predict the product lifetime at the normal use stress level, especially for highly reliable products. Two kinds of the lifetime prediction based on Gamma processes were studied. One was to predict the lifetime of the population from accelerated degradation data, and the other was to predict the lifetime of an individual by taking the accelerated degradation data as prior information. For an extensive application, the Gamma process with a time transformation and random effects was considered. A novel contribution is that a deducing method for determining the relationships between the shape and scale parameters of Gamma processes and accelerated stresses was presented. When predicting the lifetime of an individual, Bayesian inference methods were adopted to improve the prediction accuracy, in which the conjugate prior distribution and the non-conjugate prior distribution of random parameters were studied. The conjugate prior distribution only considers the random effect of the scale parameter while the non-conjugate prior distribution considers the random effects of both the scale and shape parameter. The application and usefulness of the proposed method was demonstrated by the accelerated degradation data of carbon-film resistors.
基金Projects(51475462,61374138,61370031)supported by the National Natural Science Foundation of China
文摘Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.
文摘In this paper, we have discussed a random censoring test with incomplete information, and proved that the maximum likelihood estimator(MLE) of the parameter based on the randomly censored data with incomplete information in the case of the exponential distribution has the strong consistency.
文摘Maximum Likelihood （ML） method has an excellent performance for Direction-Of-Arrival （DOA） estimation, but a mul- tidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony （ABC） algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the be- havior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the con- ventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio （SNR）, and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investi- gated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.
文摘This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the sample. It is shown that the adaptive estimator defined in this paper is asymptotically most efficient in the sense that it is asymptotic normal, and the covariance matrix of the limit distribution coincides with the one for the quasi-likelihood estimator for the case that the covariance matrix of the response variable is completely known.
基金supported by the Natural Science Foundation of Beijing City(Grant No.1042002)Technology Development Plan Project of Beijing Education Committee(Grant No.KM2005 10005009)+1 种基金the Special Grants of Beijing for Talents(Grant No.20041D0501515)supported by a grant from the Research Grants Council of Hong Kong,Hong Kong(Grant No.HKU7060/04P).
文摘In this paper, a partially linear single-index model is investigated, and three empirical log-likelihood ratio statistics for the unknown parameters in the model are suggested. It is proved that the proposed statistics are asymptotically standard chi-square under some suitable conditions, and hence can be used to construct the confidence regions of the parameters. Our methods can also deal with the confidence region construction for the index in the pure single-index model. A simulation study indicates that, in terms of coverage probabilities and average areas of the confidence regions, the proposed methods perform better than the least-squares method.
基金China Postdoctoral Science Foundation Funded Project (20080430633)Shanghai Postdoctoral Scientific Program (08R214121)+3 种基金the National Natural Science Foundation of China (10871013)the Research Fund for the Doctoral Program of Higher Education (20070005003)the Natural Science Foundation of Beijing (1072004)the Basic Research and Frontier Technology Foundation of He'nan (072300410090)
文摘In this paper, we consider the semiparametric regression model for longitudinal data. Due to the correlation within groups, a generalized empirical log-likelihood ratio statistic for the unknown parameters in the model is suggested by introducing the working covariance matrix. It is proved that the proposed statistic is asymptotically standard chi-squared under some suitable conditions, and hence it can be used to construct the confidence regions of the parameters. A simulation study is conducted to compare the proposed method with the generalized least squares method in terms of coverage accuracy and average lengths of the confidence intervals.
文摘This article provides a brief overview of various approaches that may be utilized for the analysis of human semen test results. Reference intervals are the most widely used tool for the interpretation of clinical laboratory results. Reference interval development has classically relied on concepts elaborated by the International Federation of Clinical Chemistry Expert Panel on Reference Values during the 1980s. These guidelines involve obtaining and classifying samples from a healthy population of at least 120 individuals and then identifying the outermost 5% of observations to use in defining limits for two-sided or one-sided reference intervals. More recently, decision limits based on epidemiological outcome analysis have also been introduced to aid in test interpretation. The reference population must be carefully defined on the basis of the intended clinical use of the underlying test. To determine appropriate reference intervals for use in male fertility assessment, a reference population of men with documented time to pregnancy of 〈 12 months would be most suitable. However, for epidemiological assessment of semen testing results, a reference population made up ofunselected healthy men would be preferred. Although reference and decision limits derived for individual semen analysis test results will undoubtedly be the interpretational tools of choice in the near future, in the long term, multivariate methods for the interpretation of semen analysis alone or in combination with information from the female partner seem to represent better means for assessing the likelihood of achieving a successful pregnancy in a subfertile couple.
文摘The limit properties of the dependent sequence of absolutely continuous random variables are investigated by using the notion of likelihood ratio, and a class of strong limit theorems, represented by inequalities, i.e. the strong deviation theorems, are obtained. In the proof an approach of applying the Laplace transformation to the investigation of the strong limit theorems is proposed.
基金Chuanhua Wei’s research was supported by the National Natural Science Foundation of China(11301565)Jin Yang’s research was supported by the Post-doctoral Fellowship of Nankai University
文摘As an extension of partially linear models and additive models, partially linear additive model is useful in statistical modelling. This paper proposes an empirical likelihood based approach for testing serial correlation in this semiparametric model. The proposed test method can test not only zero first-order serial correlation, but also higher-order serial correlation. Under the null hypothesis of no serial correlation, the test statistic is shown to follow asymptotically a chi-square distribution. Furthermore, a simulation study is conducted to illustrate the performance of the proposed method.
基金supported by the National Science Foundation of China under Grant Nos.11571133 and11461027the Fundamental Research Funds for the Central Universities under Grant No.20205001515
文摘This paper studies a maximum likelihood estimator(MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling(RSS). The authors first find the optimal RSS according to the character of the family, viz, arrange the RSS based on quasi complete and sufficient statistic of independent and identically distributed(iid) samples. Then under this RSS, some sufficient conditions for the existence and uniqueness of the MLE, which are easily used in practice,are obtained. Using these conditions, the existence and uniqueness of the MLEs of the parameters for some usual distributions in this family are proved. Numerical simulations for these distributions fully support the result from the above two step optimizations of the sampling and the estimation method.
基金This work was supported by Shanghai Municipal Committee of Science and Technology through grant 03DZ05052.
文摘Objective To determine the best statistical distribution of concentration data of major air pollutants in Shanghai. Methods Four types of theoretic distributions (lognormal, gamma, Pearson V and extreme value) were chosen to fit daily average concentration data of PM10, SO2 and NO2 from June 1, 2000 to May 31, 2003 in Shanghai by using the maximum likelihood method. The fit results were evaluated by Chi-square test. Results The best-fit distributions for PM10,SO2 and NO2 concentrations in Shanghai were lognormal, Pearson V, and extreme value distributions, respectively. Conclusion The results can be further applied to local air pollution prediction and control, e.g., the probabilities exceeding the air quality standard and emission source reduction of air pollutant concentration to meet the standard.
基金supported by the Health and Family Planning Commission&National Major Scientific and Technological Special Project(2014ZX09304307)
文摘The method has been developed to accurately identify the magnitude of health risks and provide scientific evidence for implementation of risk management in food safety.It combines two parameters including consequence and likelihood of adverse effects based on risk matrix.Score definitions and classification for the consequence and the likelihood of adverse effects are proposed.The risk score identifies the intersection of consequence and likelihood in risk matrix represents its health risk level with different colors：‘low＇,‘medium＇,‘high＇.Its use in an actual case is shown.
基金国家自然科学基金，the Forestry Science and TechnologyResearch Planning of Guangdong Province of China，中国科学院知识创新工程项目
文摘: Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an evergreen mixed forest in the Dinghushan Biosphere Reserve, South China. Plants in the tree, shrub and herb layers in 25 quadrats of 20 m× 20 m, 5 m× 5 m, and 1 m× 1 m were surveyed. Results indicated that: (i) for each layer, the observed species abundance with a similarly small median, mode, and a variance larger than the mean was reverse J-shaped and followed well the zero-truncated Poisson lognormal; (ii) the coefficient of variation, skewness and kurtosis of abundance, and two Poisson lognormal parameters (& and μ) for shrub layer were closer to those for the herb layer than those for the tree layer; and (iii) from the tree to the shrub to the herb layer, the α and the coefficient of variation decreased, whereas diversity increased. We suggest that: (i) the species abundance distributions in the three layers reflects the overall community characteristics; (ii) the Poisson lognormal can describe the species abundance distribution in diverse communities with a few abundant species but many rare species; and (iii) 1/α should be an alternative measure of diversity.
基金supported by Joint Foundation of and China Academy of Engineering Physical (10676006)
文摘To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
