Unlike height-diameter equations for standing trees commonly used in forest resources modelling,tree height models for cut-to-length(CTL)stems tend to produce prediction errors whose distributions are not conditionall...Unlike height-diameter equations for standing trees commonly used in forest resources modelling,tree height models for cut-to-length(CTL)stems tend to produce prediction errors whose distributions are not conditionally normal but are rather leptokurtic and heavy-tailed.This feature was merely noticed in previous studies but never thoroughly investigated.This study characterized the prediction error distribution of a newly developed such tree height model for Pin us radiata(D.Don)through the three-parameter Burr TypeⅫ(BⅫ)distribution.The model’s prediction errors(ε)exhibited heteroskedasticity conditional mainly on the small end relative diameter of the top log and also on DBH to a minor extent.Structured serial correlations were also present in the data.A total of 14 candidate weighting functions were compared to select the best two for weightingεin order to reduce its conditional heteroskedasticity.The weighted prediction errors(εw)were shifted by a constant to the positive range supported by the BXII distribution.Then the distribution of weighted and shifted prediction errors(εw+)was characterized by the BⅫdistribution using maximum likelihood estimation through 1000 times of repeated random sampling,fitting and goodness-of-fit testing,each time by randomly taking only one observation from each tree to circumvent the potential adverse impact of serial correlation in the data on parameter estimation and inferences.The nonparametric two sample Kolmogorov-Smirnov(KS)goodness-of-fit test and its closely related Kuiper’s(KU)test showed the fitted BⅫdistributions provided a good fit to the highly leptokurtic and heavy-tailed distribution ofε.Random samples generated from the fitted BⅫdistributions ofεw+derived from using the best two weighting functions,when back-shifted and unweighted,exhibited distributions that were,in about97 and 95%of the 1000 cases respectively,not statistically different from the distribution ofε.Our results for cut-tolength P.radiata stems represented the first case of any tree species where a non-normal error distribution in tree height prediction was described by an underlying probability distribution.The fitted BXII prediction error distribution will help to unlock the full potential of the new tree height model in forest resources modelling of P.radiata plantations,particularly when uncertainty assessments,statistical inferences and error propagations are needed in research and practical applications through harvester data analytics.展开更多
Spatial heterogeneity and stability are fundamental indices for describing vegetation communities. The spatial distribution characteristics of the vegetation in Nenjiang region of northeastern China were evaluated usi...Spatial heterogeneity and stability are fundamental indices for describing vegetation communities. The spatial distribution characteristics of the vegetation in Nenjiang region of northeastern China were evaluated using a variance power-law model. The data fits the model well with estimates given for the levels of heterogeneity for not only single species but also the community as a whole. The linear regression indicates that the species in the community exhibit a consistently organized spatial pattern, as is often discovered in field surveys but rarely seen in artificial systems. The species deviations from the regression line, which exhibit a leptokurtic distribution, may reflect the variability of the community. Thus, the model provides a general tool for management and regulation of ecosystems, especially where there is human disturbances.展开更多
In this study,we aim at developing a model for option pricing to reduce the risks associated with Ethiopian coffee price fluctuations.We used daily closed Washed Sidama class A Grade3(WSDA3)coffee price recorded in th...In this study,we aim at developing a model for option pricing to reduce the risks associated with Ethiopian coffee price fluctuations.We used daily closed Washed Sidama class A Grade3(WSDA3)coffee price recorded in the period 31 May 2011 to 30 March 2018 obtained from Ethiopia commodity exchange(ECX)market to analyse the price fluctuation.The nature of log-returns of the price is asymmetric(negatively skewed)and exhibits high kurtosis.We used jump diffusion models for modeling and option pricing the coffee price.The method of maximum likelihood is applied to estimate the parameters of the models.We used the root mean square error(RMSE)to test the validation of the models.The values of RMSE for Merton’s and double exponential jump diffusion models are 0.1093 and 0.0783,respectively.These results indicate that the models fit the data very well.We used analytical and Monte Carlo technique to find the call option pricing of WSDA3 price.Based on the empirical results,we concluded that double exponential jump diffusion model is more efficient than Merton’s model for modeling and option pricing of this coffee price.展开更多
文摘Unlike height-diameter equations for standing trees commonly used in forest resources modelling,tree height models for cut-to-length(CTL)stems tend to produce prediction errors whose distributions are not conditionally normal but are rather leptokurtic and heavy-tailed.This feature was merely noticed in previous studies but never thoroughly investigated.This study characterized the prediction error distribution of a newly developed such tree height model for Pin us radiata(D.Don)through the three-parameter Burr TypeⅫ(BⅫ)distribution.The model’s prediction errors(ε)exhibited heteroskedasticity conditional mainly on the small end relative diameter of the top log and also on DBH to a minor extent.Structured serial correlations were also present in the data.A total of 14 candidate weighting functions were compared to select the best two for weightingεin order to reduce its conditional heteroskedasticity.The weighted prediction errors(εw)were shifted by a constant to the positive range supported by the BXII distribution.Then the distribution of weighted and shifted prediction errors(εw+)was characterized by the BⅫdistribution using maximum likelihood estimation through 1000 times of repeated random sampling,fitting and goodness-of-fit testing,each time by randomly taking only one observation from each tree to circumvent the potential adverse impact of serial correlation in the data on parameter estimation and inferences.The nonparametric two sample Kolmogorov-Smirnov(KS)goodness-of-fit test and its closely related Kuiper’s(KU)test showed the fitted BⅫdistributions provided a good fit to the highly leptokurtic and heavy-tailed distribution ofε.Random samples generated from the fitted BⅫdistributions ofεw+derived from using the best two weighting functions,when back-shifted and unweighted,exhibited distributions that were,in about97 and 95%of the 1000 cases respectively,not statistically different from the distribution ofε.Our results for cut-tolength P.radiata stems represented the first case of any tree species where a non-normal error distribution in tree height prediction was described by an underlying probability distribution.The fitted BXII prediction error distribution will help to unlock the full potential of the new tree height model in forest resources modelling of P.radiata plantations,particularly when uncertainty assessments,statistical inferences and error propagations are needed in research and practical applications through harvester data analytics.
基金Supported by the Japan Society for the Promotion of Science (No. L-02711)
文摘Spatial heterogeneity and stability are fundamental indices for describing vegetation communities. The spatial distribution characteristics of the vegetation in Nenjiang region of northeastern China were evaluated using a variance power-law model. The data fits the model well with estimates given for the levels of heterogeneity for not only single species but also the community as a whole. The linear regression indicates that the species in the community exhibit a consistently organized spatial pattern, as is often discovered in field surveys but rarely seen in artificial systems. The species deviations from the regression line, which exhibit a leptokurtic distribution, may reflect the variability of the community. Thus, the model provides a general tool for management and regulation of ecosystems, especially where there is human disturbances.
文摘In this study,we aim at developing a model for option pricing to reduce the risks associated with Ethiopian coffee price fluctuations.We used daily closed Washed Sidama class A Grade3(WSDA3)coffee price recorded in the period 31 May 2011 to 30 March 2018 obtained from Ethiopia commodity exchange(ECX)market to analyse the price fluctuation.The nature of log-returns of the price is asymmetric(negatively skewed)and exhibits high kurtosis.We used jump diffusion models for modeling and option pricing the coffee price.The method of maximum likelihood is applied to estimate the parameters of the models.We used the root mean square error(RMSE)to test the validation of the models.The values of RMSE for Merton’s and double exponential jump diffusion models are 0.1093 and 0.0783,respectively.These results indicate that the models fit the data very well.We used analytical and Monte Carlo technique to find the call option pricing of WSDA3 price.Based on the empirical results,we concluded that double exponential jump diffusion model is more efficient than Merton’s model for modeling and option pricing of this coffee price.
