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具有ARMA扰动的回归模型的最大似然估计AI 解读

The regression model with autoregressive-moving average disturbances may be cast in a form suitable for the application of Kalman filtering techniques. This enables the generalized least squares estimator to be calculated without evaluating and inverting the covariance matrix of the disturbances. The problem of forecasting future values of the dependent variable is also effectively solved when the Kalman filter technique is applied. Furthermore, the properties of the…

回归分析中序列相关的简单检验AI 解读

An exact test for serial correlation in regression models is proposed based on the fact that under classical assumptions and including normality for disturbances, the successive quantities are independent N(0, σ2). For various types of data the power of the proposed test compares favorably with that of the BLUS test, but neither test is as powerful as the full Durbin-Watson procedure in which an approximate significance point is calculated when the bounds test is…