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一、序列相关性的概念——违反基本假设的定义及违反的原因 二、序列相关性的后果——违反基本假设会造成什么样的后果 三、序列相关性的检验——怎样诊断是否违反基本假设 四、具有序列相关性模型的估计——如何消除或减弱对基本假设的违反 五、案例
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• 回归分析概述 • 双变量线性回归模型的参数估计 • 双变量线性回归模型的假设检验 • 双变量线性回归模型的预测 • 实例
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时间序列数据或截面数据都是一维数据。例如时间序列数据是变量按时间得到的数据;截面数据是变量在截面空间上的数据。面板数据是同时在时间和截面上取得的二维数据。所以,面板数据(panel data)也称时间序列截面数据(time series and cross section data)或混合数据(pool data)
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3.1 多元线性回归模型 3.2 回归参数的估计 3.3 参数估计量的性质 3.4 回归方程的显著性检验 3.5 中心化和标准化 3.6 相关阵与偏相关系数 3.7 本章小结与评注
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The models we discussed are models that are linear in parameters; variables Y and Xs do not necessarily have to be linear The price elasticity of demand~the log-linear models The rate of growth~semilog model Functional forms of regression models which are linear in parameters, but not necessarily linear in variables:
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Assumptions of the classical Linear Model (Clm) e So far, we know that given the Gauss Markov assumptions, OLS IS BLUE e In order to do classical hypothesis testing we need to add another assumption(beyond the Gauss-Markov assumptions) Assume that u is independent of x,x2…,xk and u is normally distributed with zero mean and variance 0: u- Normal(0, 02) Economics 20- Prof anderson
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The Normal Distribution: the distribution of a continuous r.v. whose value depends on a number of factors, yet no single factor dominates the other. 1. Properties of the normal distribution: 1)The normal distribution curve is symmetrical around its mean valueu. 2)The PDF of the distribution is the highest at its mean value but tails off at its extremities
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What is Heteroskedasticity Recall the assumption of homoskedastic implied that conditional on the explanator variables the variance of the unobserved error u was constant If this is not true that is if the variance of u is different for different values of thex's. then the errors are heteroskedastic
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Definition (1) Econometrics: economic measurement. (2) Econometrics: the social science in which the tools of economic theory, mathematics, and statistical inference are applied to the analysis of economic phenomena. (3) Econometrics: the result of a certain outlook on the role of economics, consists of the application of mathematical statistics to economic data to lend
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Time series vs Cross sectional e Time series data has a temporal ordering unlike cross-section data Will need to alter some of our assumptions to take into account that we no longer have a random sample of individuals Instead. we have one realization of a stochastic(i.e. random) process Economics 20- Prof anderson
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