MICEData.plot_fit_obs()

statsmodels.imputation.mice.MICEData.plot_fit_obs

MICEData.plot_fit_obs(col_name, lowess_args=None, lowess_min_n=40, jitter=None, plot_points=True, ax=None) [source]

Plot fitted versus imputed or observed values as a scatterplot.

Parameters:

col_name : string The variable to be plotted on the horizontal axis. lowess_args : dict-like Keyword arguments passed to lowess fit. A dictionary of dictionaries, keys are ‘o’ and ‘i’ denoting ‘observed’ and ‘imputed’, respectively. lowess_min_n : integer Minimum sample size to plot a lowess fit jitter : float or tuple Standard deviation for jittering points in the plot. Either a single scalar applied to both axes, or a tuple containing x-axis jitter and y-axis jitter, respectively. plot_points : bool If True, the data points are plotted. ax : matplotlib axes object Axes on which to plot, created if not provided.

Returns:

The matplotlib figure on which the plot is drawn.