一、一元线性回归模型的基本假设 二、参数的普通最小二乘估计(OLS) 三、参数估计的最大或然法(ML) 四、最小二乘估计量的性质 五、参数估计量的概率分布及随机干扰项方差的估计
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1 An Excursion into Non-linearity land Motivation: the linear structural (and time series) models cannot explain a number of important features common to much financial data
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1 Stationarity and unit Root testing WHy do we need to test for Non-Stationarity? The stationarity or otherwise of a series can strongly influence its behaviour and properties -e.g. persistence of shocks will be infinite for nonstationary series Spurious regressions. If two variables are trending over
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1 Motivations All the models we have looked at thus far have been single equations models of the form y=XB+u All of the variables con
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