摘要翻译:
本文介绍了一种基于周期图和谱估计方程的经验似然法。该公式通过数据变换(即傅立叶变换)处理相关数据,并根据谱分布而不是时域概率分布来发展。研究了线性时间过程的频域经验似然的渐近性质。该方法得到的似然比可以用来为一类归一化(或比率)谱参数(包括自相关)建立非参数的渐近校正置信域。最大经验似然估计是可能的,以及谱矩条件的检验。该方法可用于Whittle估计和拟合优度检验等推理问题。
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英文标题:
《A frequency domain empirical likelihood for short- and long-range
dependence》
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作者:
Daniel J. Nordman, Soumendra N. Lahiri
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最新提交年份:
2007
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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: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 introduces a version of empirical likelihood based on the periodogram and spectral estimating equations. This formulation handles dependent data through a data transformation (i.e., a Fourier transform) and is developed in terms of the spectral distribution rather than a time domain probability distribution. The asymptotic properties of frequency domain empirical likelihood are studied for linear time processes exhibiting both short- and long-range dependence. The method results in likelihood ratios which can be used to build nonparametric, asymptotically correct confidence regions for a class of normalized (or ratio) spectral parameters, including autocorrelations. Maximum empirical likelihood estimators are possible, as well as tests of spectral moment conditions. The methodology can be applied to several inference problems such as Whittle estimation and goodness-of-fit testing.
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PDF链接:
https://arxiv.org/pdf/708.0197