估计理论
数学
估计员
非线性系统
统计
最大似然
估计
计算机科学
最大似然序列估计
应用数学
非线性回归
回归分析
回归
线性回归
期望最大化算法
出处
期刊:International Conference on Acoustics, Speech, and Signal Processing
日期:1984-03-19
卷期号:9: 271-274
被引量:99
标识
DOI:10.1109/icassp.1984.1172397
摘要
Statistical properties of certain parametric array processing methods are investigated. Asymptotic normality of Fourier-transformed sensor outputs for usual signal plus noise models is applied to define likelihood functions which have to be maximized for parameter estimation. In the first well known approach, the parameter structure is contained in the spectral density matrix of the outputs. The second likelihood function is conditional and results in a nonlinear regression problem. Since the likelihood equations are difficult to solve in general, properties of approximate solutions, for example Liggett's method, are of interest. Asymptotic distributions of the estimates and their approximations and results of some numerical experiments are discussed.
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