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gung - Reinstate Monica
gung - Reinstate Monica
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I'm new to regression (vector autoregression), and recently encountered the following issue:

  1. If I use raw dependent and independent variables to do the regression, the $R^2$, DW-d test and standard error of estimate for each dependent variable are quite good. The $R^2$ is above $95\%$.

  2. However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The $R^2$ ranges from $60\%-90\%$.

So what happened after I normalized the data? Much thanks.

I'm new to regression (vector autoregression), and recently encountered the following issue:

  1. If I use raw dependent and independent variables to do the regression, the $R^2$, DW-d test and standard error of estimate for each dependent variable are quite good. The $R^2$ is above $95\%$.

  2. However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The $R^2$ ranges from $60\%-90\%$.

So what happened after I normalized the data? Much thanks.

I'm new to regression (vector autoregression), and recently encountered the following issue:

  1. If I use raw dependent and independent variables to do the regression, the $R^2$, DW-d test and standard error of estimate for each dependent variable are quite good. The $R^2$ is above $95\%$.

  2. However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The $R^2$ ranges from $60\%-90\%$.

So what happened after I normalized the data?

Formatted list; Corrected some spelling
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edit approved Dec 25, 2013 at 22:31
user35743
edit approved Dec 25, 2013 at 22:31
user35743

normalized the data Normalizing to zero mean and unit variance before regression

I'm new to regression (vector autoregression), and recently encountered such issues： 1)when I use raw dependent and independent variables to do the regression, the R^2, DW-d test and standard error of estimate for each dependent variable are quite good. The R^2 are above 95%. 2) However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The R^2 ranges from 60%-90%. Sofollowing issue:

  1. If I use raw dependent and independent variables to do the regression, the $R^2$, DW-d test and standard error of estimate for each dependent variable are quite good. The $R^2$ is above $95\%$.

  2. However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The $R^2$ ranges from $60\%-90\%$.

So what happened after I normalized the data??? Much thanks.

normalized the data to zero mean and unit variance before regression

I'm new to regression (vector autoregression), and recently encountered such issues： 1)when I use raw dependent and independent variables to do the regression, the R^2, DW-d test and standard error of estimate for each dependent variable are quite good. The R^2 are above 95%. 2) However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The R^2 ranges from 60%-90%. So what happened after I normalized the data??? Much thanks.

Normalizing to zero mean and unit variance before regression

I'm new to regression (vector autoregression), and recently encountered the following issue:

  1. If I use raw dependent and independent variables to do the regression, the $R^2$, DW-d test and standard error of estimate for each dependent variable are quite good. The $R^2$ is above $95\%$.

  2. However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The $R^2$ ranges from $60\%-90\%$.

So what happened after I normalized the data? Much thanks.

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GodoorSun
GodoorSun
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normalized the data to zero mean and unit variance before regression

I'm new to regression (vector autoregression), and recently encountered such issues： 1)when I use raw dependent and independent variables to do the regression, the R^2, DW-d test and standard error of estimate for each dependent variable are quite good. The R^2 are above 95%. 2) However, When the dependent and independent variables are normalized to zero mean and unit variables (column normalized), these measures got worse. The R^2 ranges from 60%-90%. So what happened after I normalized the data??? Much thanks.