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  2. Partial regression plot - Wikipedia

    en.wikipedia.org/wiki/Partial_regression_plot

    The residuals from the least squares linear fit to this plot are identical to the residuals from the least squares fit of the original model (Y against all the independent variables including Xi). The influences of individual data values on the estimation of a coefficient are easy to see in this plot.

  3. Partial residual plot - Wikipedia

    en.wikipedia.org/wiki/Partial_residual_plot

    Residuals = residuals from the full model, ^ = regression coefficient from the i-th independent variable in the full model, X i = the i-th independent variable. Partial residual plots are widely discussed in the regression diagnostics literature (e.g., see the References section below).

  4. Regression validation - Wikipedia

    en.wikipedia.org/wiki/Regression_validation

    An illustrative plot of a fit to data (green curve in top panel, data in red) plus a plot of residuals: red points in bottom plot. Dashed curve in bottom panel is a straight line fit to the residuals. If the functional form is correct then there should be little or no trend to the residuals - as seen here.

  5. Plot (graphics) - Wikipedia

    en.wikipedia.org/wiki/Plot_(graphics)

    Partial regression plots are also referred to as added variable plots, adjusted variable plots, and individual coefficient plots. Partial residual plot : In applied statistics, a partial residual plot is a graphical technique that attempts to show the relationship between a given independent variable and the response variable given that other ...

  6. Durbin–Watson statistic - Wikipedia

    en.wikipedia.org/wiki/Durbin–Watson_statistic

    In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation at lag 1 in the residuals (prediction errors) from a regression analysis. It is named after James Durbin and Geoffrey Watson. The small sample distribution of this ratio was derived by John von Neumann (von Neumann, 1941).

  7. Leverage (statistics) - Wikipedia

    en.wikipedia.org/wiki/Leverage_(statistics)

    where is the index of independent variable, is the index of observation and [] are the residuals from regressing against the remaining independent variables. Note that the partial leverage is the leverage of the i t h {\displaystyle {i}^{th}} point in the partial regression plot for the j t h {\displaystyle {j}^{th}} variable.

  8. Studentized residual - Wikipedia

    en.wikipedia.org/wiki/Studentized_residual

    On the other hand, the internally studentized residuals are in the range , where ν = n − m is the number of residual degrees of freedom. If t i represents the internally studentized residual, and again assuming that the errors are independent identically distributed Gaussian variables, then: [2]

  9. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.