设{Xn,n≥1}是一均值为零、方差有限的正相伴平稳序列.记Sn=sum Xk,Mn=maxx≤n|Sk|,n≥1 from k=1 to n,并假设0<σ2=EX12+2 sum E X1 Xk<∞ from k=2 to ∞.在E|X1|2+δ<∞,δ∈(0,1],以及对某个α>1,sum Cov(X1,Xj)=O(n-...设{Xn,n≥1}是一均值为零、方差有限的正相伴平稳序列.记Sn=sum Xk,Mn=maxx≤n|Sk|,n≥1 from k=1 to n,并假设0<σ2=EX12+2 sum E X1 Xk<∞ from k=2 to ∞.在E|X1|2+δ<∞,δ∈(0,1],以及对某个α>1,sum Cov(X1,Xj)=O(n-α) from j=n+1 to ∞的条件下,建立了PA序列关于Chung型对数律的精确收敛速度.展开更多
Empirical Euclidean likelihood for general estimating equations for association dependent processes is investigated. The strong consistency and asymptotic normality of the blockwise maximum empirical Euclidean likelih...Empirical Euclidean likelihood for general estimating equations for association dependent processes is investigated. The strong consistency and asymptotic normality of the blockwise maximum empirical Euclidean likelihood estimator are presented. We show that it is more efficient than estimator without blocking. The blockwise empirical Euclidean log-likelihood ratio asymptotically follows a chi-square distribution.展开更多
Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of mi...Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of microtopography on two shady slopes（slope A,5 hm2,uniform slope;slope B,5 hm2,microtopography slope） and surveyed the height,the diameter at breast height and the location（x,y coordinates） of all selected individual trees（Robinia pseudoacacia Linn.,Pyrus betulifolia Bunge,Populus hopeiensis Hu ＆ Chow,Armeniaca sibirica Lam.,Populus simonii Carr.and Ulmus pumila Linn.） on slope A and slope B in the watersheds of Wuqi county,Shaanxi province.Subsequently,the effects of microtopography on the spatial pattern of forest stands were analyzed using Ripley＇s K（r） function.The results showed that：（1） The maximal aggregation radiuses of the tree species on the uniform slope（slope A） were larger than 40 m,whereas those of the tree species on the microtopography slope（slope B） were smaller than 30 m.（2） On slope B,the spatial association of R.pseudoacacia with P.betulifolia,A.sibirica,P.simonii and U.pumila varied from being strongly negative to positive at microtopography scales.The spatial association of Populus hopeiensis Hu ＆ Chow with U.pumila also varied from being strongly negative to positive at microtopography scales.However,there was no spatial association between P.betulifolia and P.hopeiensis,P.betulifolia and A.sibirica,P.betulifolia and P.simonii,P.betulifolia and U.pumila,P.hopeiensis and A.sibirica,P.hopeiensis and P.simonii,A.sibirica and P.simonii,A.sibirica and U.pumila,and P.simonii and U.pumila.On slope A,the spatial association between tree species were strongly negative.The results suggest that microtopography may shape tree distribution patterns on the semi-arid Loess Plateau.展开更多
The empirical likelihood is used to propose a new class of quantile estimators in the presence of some auxiliary information under positively associated samples. It is shown that the proposed quantile estimators are a...The empirical likelihood is used to propose a new class of quantile estimators in the presence of some auxiliary information under positively associated samples. It is shown that the proposed quantile estimators are asymptotically normally distributed with smaller asymptotic variances than those of the usual quantile estimators.展开更多
Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to...Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.展开更多
AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scal...AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scale is a measure which precisely describes the severity of the SCI.However, it has various limitations which lead to incomplete assessment of SCI patients.We have developed a 63 point scoring system, i.e., NFS for patients suffering with SCI.A list of symptoms either common or rare that were found to be associated with SCI was recorded for each patient.On the basis of these lists, we have developed NFS.RESULTS These lists served as a base to prepare NFS, a 63 point positional(each symptom is sub-graded and get points based on position) and directional(moves in direction BAD → GOOD) scoring system.For non-progressive diseases, 1, 2, 3, 4, 5 denote worst, bad, moderate, good and best(normal), respectively.NFS for SCI has been divided into different groups based on the affected part of the body being assessed, i.e., motor assessment(shoulders, elbow, wrist, fingers-grasp, fingers-release, hip, knee, ankle and toe), sensory assessment, autonomic assessment, bed sore assessment and general assessment.As probability based studies required a range of(-1, 1) or at least the range of(0, 1) to be useful for real world analysis, the grades were converted to respective numeric values.CONCLUSION NFS can be considered as a unique tool to assess the improvement in patients with SCI as it overcomes the limitations of ASIA impairment scale.展开更多
Association rules mining is a major data mining field that leads to discovery of associations and correlations among items in today’s big data environment. The conventional association rule mining focuses mainly on p...Association rules mining is a major data mining field that leads to discovery of associations and correlations among items in today’s big data environment. The conventional association rule mining focuses mainly on positive itemsets generated from frequently occurring itemsets (PFIS). However, there has been a significant study focused on infrequent itemsets with utilization of negative association rules to mine interesting frequent itemsets (NFIS) from transactions. In this work, we propose an efficient backward calculating negative frequent itemset algorithm namely EBC-NFIS for computing backward supports that can extract both positive and negative frequent itemsets synchronously from dataset. EBC-NFIS algorithm is based on popular e-NFIS algorithm that computes supports of negative itemsets from the supports of positive itemsets. The proposed algorithm makes use of previously computed supports from memory to minimize the computation time. In addition, association rules, i.e. positive and negative association rules (PNARs) are generated from discovered frequent itemsets using EBC-NFIS algorithm. The efficiency of the proposed algorithm is verified by several experiments and comparing results with e-NFIS algorithm. The experimental results confirm that the proposed algorithm successfully discovers NFIS and PNARs and runs significantly faster than conventional e-NFIS algorithm.展开更多
文摘设{Xn,n≥1}是一均值为零、方差有限的正相伴平稳序列.记Sn=sum Xk,Mn=maxx≤n|Sk|,n≥1 from k=1 to n,并假设0<σ2=EX12+2 sum E X1 Xk<∞ from k=2 to ∞.在E|X1|2+δ<∞,δ∈(0,1],以及对某个α>1,sum Cov(X1,Xj)=O(n-α) from j=n+1 to ∞的条件下,建立了PA序列关于Chung型对数律的精确收敛速度.
基金Supported by the National Natural Science Foundation of China(11461057)the Natural Science Foundation of Guangxi(2014GXNSFBA118011)the Science Foundation of Guangxi Education Department(ZD2014120)
基金Supported by the National Natural Science Foundation of China (10771192)the Zhejiang Natural Science Foundation (J20091364)
文摘Empirical Euclidean likelihood for general estimating equations for association dependent processes is investigated. The strong consistency and asymptotic normality of the blockwise maximum empirical Euclidean likelihood estimator are presented. We show that it is more efficient than estimator without blocking. The blockwise empirical Euclidean log-likelihood ratio asymptotically follows a chi-square distribution.
基金financially supported by China National Scientific and Technical Innovation Research Project for 12~(th) Five Year Plan (2011BAD38B0601)the National Natural Science Foundation of China (41472313)the Natural Science Foundation of Shandong Province (ZR2011DM012,ZR2014DL002)
文摘Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of microtopography on two shady slopes（slope A,5 hm2,uniform slope;slope B,5 hm2,microtopography slope） and surveyed the height,the diameter at breast height and the location（x,y coordinates） of all selected individual trees（Robinia pseudoacacia Linn.,Pyrus betulifolia Bunge,Populus hopeiensis Hu ＆ Chow,Armeniaca sibirica Lam.,Populus simonii Carr.and Ulmus pumila Linn.） on slope A and slope B in the watersheds of Wuqi county,Shaanxi province.Subsequently,the effects of microtopography on the spatial pattern of forest stands were analyzed using Ripley＇s K（r） function.The results showed that：（1） The maximal aggregation radiuses of the tree species on the uniform slope（slope A） were larger than 40 m,whereas those of the tree species on the microtopography slope（slope B） were smaller than 30 m.（2） On slope B,the spatial association of R.pseudoacacia with P.betulifolia,A.sibirica,P.simonii and U.pumila varied from being strongly negative to positive at microtopography scales.The spatial association of Populus hopeiensis Hu ＆ Chow with U.pumila also varied from being strongly negative to positive at microtopography scales.However,there was no spatial association between P.betulifolia and P.hopeiensis,P.betulifolia and A.sibirica,P.betulifolia and P.simonii,P.betulifolia and U.pumila,P.hopeiensis and A.sibirica,P.hopeiensis and P.simonii,A.sibirica and P.simonii,A.sibirica and U.pumila,and P.simonii and U.pumila.On slope A,the spatial association between tree species were strongly negative.The results suggest that microtopography may shape tree distribution patterns on the semi-arid Loess Plateau.
基金supported by the National Natural Science Foundation of China(11271088,11361011,11201088)the Natural Science Foundation of Guangxi(2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001)
文摘The empirical likelihood is used to propose a new class of quantile estimators in the presence of some auxiliary information under positively associated samples. It is shown that the proposed quantile estimators are asymptotically normally distributed with smaller asymptotic variances than those of the usual quantile estimators.
基金This research was supported by the National Natural Science Foundation of China under Grant No.61772280by the China Special Fund for Meteorological Research in the Public Interest under Grant GYHY201306070by the Jiangsu Province Innovation and Entrepreneurship Training Program for College Students under Grant No.201810300079X.
文摘Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.
文摘AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scale is a measure which precisely describes the severity of the SCI.However, it has various limitations which lead to incomplete assessment of SCI patients.We have developed a 63 point scoring system, i.e., NFS for patients suffering with SCI.A list of symptoms either common or rare that were found to be associated with SCI was recorded for each patient.On the basis of these lists, we have developed NFS.RESULTS These lists served as a base to prepare NFS, a 63 point positional(each symptom is sub-graded and get points based on position) and directional(moves in direction BAD → GOOD) scoring system.For non-progressive diseases, 1, 2, 3, 4, 5 denote worst, bad, moderate, good and best(normal), respectively.NFS for SCI has been divided into different groups based on the affected part of the body being assessed, i.e., motor assessment(shoulders, elbow, wrist, fingers-grasp, fingers-release, hip, knee, ankle and toe), sensory assessment, autonomic assessment, bed sore assessment and general assessment.As probability based studies required a range of(-1, 1) or at least the range of(0, 1) to be useful for real world analysis, the grades were converted to respective numeric values.CONCLUSION NFS can be considered as a unique tool to assess the improvement in patients with SCI as it overcomes the limitations of ASIA impairment scale.
文摘Association rules mining is a major data mining field that leads to discovery of associations and correlations among items in today’s big data environment. The conventional association rule mining focuses mainly on positive itemsets generated from frequently occurring itemsets (PFIS). However, there has been a significant study focused on infrequent itemsets with utilization of negative association rules to mine interesting frequent itemsets (NFIS) from transactions. In this work, we propose an efficient backward calculating negative frequent itemset algorithm namely EBC-NFIS for computing backward supports that can extract both positive and negative frequent itemsets synchronously from dataset. EBC-NFIS algorithm is based on popular e-NFIS algorithm that computes supports of negative itemsets from the supports of positive itemsets. The proposed algorithm makes use of previously computed supports from memory to minimize the computation time. In addition, association rules, i.e. positive and negative association rules (PNARs) are generated from discovered frequent itemsets using EBC-NFIS algorithm. The efficiency of the proposed algorithm is verified by several experiments and comparing results with e-NFIS algorithm. The experimental results confirm that the proposed algorithm successfully discovers NFIS and PNARs and runs significantly faster than conventional e-NFIS algorithm.
