Variable Latencies of Noisy Signals: Estimation and Testing in Brain Potential Data
针对脑电信号单次反应潜伏期变化的问题，提出基于最大似然的Fisher评分法估计潜伏期，并推导检验潜伏期变异性的统计量，通过模拟和真实数据验证。
The electric response of the brain related to some event, i.e. stimulus, is usually estimated by repeated stimulation and subsequent averaging of the activity recorded time-locked to the stimulus. The present paper deals with the model that the single responses may have varying latency, i.e. arrival time, after stimulus onset. For estimating the single latencies, a maximum likelihood approach employing iterative Fisher-scoring is developed. Further a statistic for testing on the presence of latency variation is derived. Simulations and real data applications are discussed.