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Inference for a Random Wavelet Packet Model of Single-Channel Event-Related Potentials

单通道事件相关电位的随机小波包模型推断

Event-related potentials (ERPs) are brain electrical potentials associated with sensory and cognitive processing. ERP researchers typically wish to separate a recorded time series into functionally distinct component waveforms, and to estimate the effects of experimental conditions on each component. We present an integrated statistical approach to the decomposition of single-channel ERPs and to inference concerning the component waveforms and the effects of experimental…

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Semiparametric Stochastic Mixed Models for Longitudinal Data

纵向数据的半参数随机混合模型

We consider inference for a semiparametric stochastic mixed model for longitudinal data. This model uses parametric fixed effects to represent the covariate effects and an arbitrary smooth function to model the time effect and accounts for the within-subject correlation using random effects and a stationary or nonstationary stochastic process. We derive maximum penalized likelihood estimators of the regression coefficients and the nonparametric function. The resulting…

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Frequency Domain Estimation of the Parameters of Human Brain Electrical Dipoles

人脑电偶极子参数的频域估计

Human brain evoked potentials are elicited by a stimulus and can be recorded by scalp electrodes. Many researchers have proposed models in which evoked potentials are generated by equivalent electrical dipoles in the brain. Each dipole is defined by a set of parameters that specify its location, orientation, and magnitude. Existing approaches to estimation of dipole parameters do not realistically account for errors resulting from background brain electrical activity…

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Frequency Domain Estimation of the Parameters of Human Brain Electrical Dipoles

人脑电偶极子参数的频域估计

Human brain evoked potentials are elicited by a stimulus and can be recorded by scalp electrodes. Many researchers have proposed models in which evoked potentials are generated by equivalent electrical dipoles in the brain. Each dipole is defined by a set of parameters that specify its location, orientation, and magnitude. Existing approaches to estimation of dipole parameters do not realistically account for errors resulting from background brain electrical activity…

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Testing for No Effect When Estimating a Smooth Function by Nonparametric Regression: A Randomization Approach

非参数平滑回归中无关联假设的随机化检验

When a linear regression function is estimated by ordinary least squares, the null hypothesis of no relationship between the response and the design variable can be tested by the normal theory F test. This article describes a new test for use in the case in which a smooth regression function is estimated by a nonparametric procedure such as kernel estimation or local regression. The test is constructed as an approximation to an exact permutation test. The test statistic is…

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