摘要翻译:
本文研究了一类指数族模型,其规范参数被指定为未知无穷维斜率函数的线性函数。建立了斜率函数估计的最优minimax收敛速度。通过参数维数随样本量增长的约束极大似然估计,构造出达到最优速率的估计量。在Le Cam的渐近等价理论的启发下,利用测度变化论来消除指数族模型的非线性所引起的偏差。
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英文标题:
《Estimation in Functional Regression for General Exponential Families》
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作者:
Winston Wei Dou, David Pollard, Harrison H. Zhou
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最新提交年份:
2011
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分类信息:
一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、
数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类:Mathematics 数学
二级分类:Functional Analysis 功能分析
分类描述:Banach spaces, function spaces, real functions, integral transforms, theory of distributions, measure theory
Banach空间,函数空间,实函数,积分变换,分布理论,测度理论
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一级分类:Mathematics 数学
二级分类:Probability 概率
分类描述:Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用:例如中心极限定理,大偏差,随机微分方程,统计力学模型,排队论
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一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
This paper studies a class of exponential family models whose canonical parameters are specified as linear functionals of an unknown infinite-dimensional slope function. The optimal minimax rates of convergence for slope function estimation are established. The estimators that achieve the optimal rates are constructed by constrained maximum likelihood estimation with parameters whose dimension grows with sample size. A change-of-measure argument, inspired by Le Cam's theory of asymptotic equivalence, is used to eliminate the bias caused by the non-linearity of exponential family models.
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PDF链接:
https://arxiv.org/pdf/1108.3552