statsmodels.graphics.regressionplots.plot_ccpr(results, exog_idx, ax=None)
[source]
Plot CCPR against one regressor.
Generates a CCPR (component and componentplusresidual) plot.
Parameters: 


Returns: 
fig – If 
Return type: 
Matplotlib figure instance 
See also
plot_ccpr_grid
The CCPR plot provides a way to judge the effect of one regressor on the response variable by taking into account the effects of the other independent variables. The partial residuals plot is defined as Residuals + B_i*X_i versus X_i. The component adds the B_i*X_i versus X_i to show where the fitted line would lie. Care should be taken if X_i is highly correlated with any of the other independent variables. If this is the case, the variance evident in the plot will be an underestimate of the true variance.
http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/ccpr.htm
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.graphics.regressionplots.plot_ccpr.html