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A three-parameter logistic regression model
《Statistical Theory and Related Fields》2021年第3期265-274,共10页Xiaoli Yu Shaoting Li Jiahua Chen 
fundings from the National Natural Science foundation of China[Grant Number 11871419];the Natural Science and Engineering Research Council of Canada.
Dose–response experiments and data analyses are often carried out according to an optimal design under a model assumption.A two-parameter logistic model is often used because of its nice mathematical properties and p...
关键词：effective dose level optimal design sequential ED-design up-and-down design vertex direction method 
Sequential Big Data-Based Macroeconomic Forecast for Industrial Value Added被引量：1
《Communications in Mathematics and Statistics》2019年第4期445-457,共13页Yunli Yang Jing Kong Lu Yang Zhouwang Yang 
The work is supported by the NSF of China(No.11871447);Anhui Initiative in Quantum Information Technologies(AHY150200).
Macroeconomic situation is the overall performance of a country’s and regional economic situation.At present,the vast majority of macroeconomic indicators are obtained through sampling surveys,step-by-step reporting,...
关键词：MACROECONOMICS Time series big data Sequential update Multivariate regression prediction 
Lattice-based sequential aggregate signatures with lazy verification被引量：4
《The Journal of China Universities of Posts and Telecommunications》2015年第6期36-44,共9页Zhang Yanhua Hu Yupu Jiang Mingming Xue Lili 
supported by the National Natural Science Foundations of China (61173151, 61472309)
This paper proposes the first lattice-based sequential aggregate signature （SAS） scheme with lazy verification that is provably secure in the random oracle model. As opposed to large integer factoring and discrete l...
关键词：sequential aggregate signatures lattice-based cryptography lazy verification small integer solution 
A sequential GM-based PHD filter for a linear Gaussian system被引量：3
《Science China(Information Sciences)》2013年第10期11-20,共10页LIU ZongXiang 
supported by National Natural Science Foundation of China(Grant No.61271107);Natural Science Foundation of Guangdong Province(Grant No.S2012010009417);Research Fund for the Doctoral Program of Higher Education of China(Grant No.20104408120001);Key Projects in the National Science & Technology Pillar Program(Grant No.2011BAH24B12)
The probability hypothesis density （PHD） filter provides an efficiently parallel processing method for multi-target tracking. However, measurements have to be gathered for a scan period before the PHD filter can per...
关键词：multi-target tracking PHD filter sequential filter Gaussian mixture linear Gaussian system 
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