class statsmodels.graphics.gofplots.ProbPlot(data, dist=<scipy.stats._continuous_distns.norm_gen object>, fit=False, distargs=(), a=0, loc=0, scale=1)
[source]
Class for convenient construction of Q-Q, P-P, and probability plots.
Can take arguments specifying the parameters for dist or fit them automatically. (See fit under kwargs.)
Parameters: |
|
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See also
scipy.stats.probplot
If fit is True then the parameters are fit using the
fit()
method.The call signatures for the qqplot, ppplot, and probplot
ppplot : Probability-Probability plot
qqplot : Quantile-Quantile plot
probplot : Probability plot
>>> import statsmodels.api as sm >>> from matplotlib import pyplot as plt
>>> # example 1 >>> data = sm.datasets.longley.load() >>> data.exog = sm.add_constant(data.exog) >>> model = sm.OLS(data.endog, data.exog) >>> mod_fit = model.fit() >>> res = mod_fit.resid # residuals >>> probplot = sm.ProbPlot(res) >>> probplot.qqplot() >>> plt.show()
qqplot of the residuals against quantiles of t-distribution with 4 degrees of freedom:
>>> # example 2 >>> import scipy.stats as stats >>> probplot = sm.ProbPlot(res, stats.t, distargs=(4,)) >>> fig = probplot.qqplot() >>> plt.show()
qqplot against same as above, but with mean 3 and std 10:
>>> # example 3 >>> probplot = sm.ProbPlot(res, stats.t, distargs=(4,), loc=3, scale=10) >>> fig = probplot.qqplot() >>> plt.show()
Automatically determine parameters for t distribution including the loc and scale:
>>> # example 4 >>> probplot = sm.ProbPlot(res, stats.t, fit=True) >>> fig = probplot.qqplot(line='45') >>> plt.show()
A second ProbPlot
object can be used to compare two seperate sample sets by using the other
kwarg in the qqplot
and ppplot
methods.
>>> # example 5 >>> import numpy as np >>> x = np.random.normal(loc=8.25, scale=2.75, size=37) >>> y = np.random.normal(loc=8.75, scale=3.25, size=37) >>> pp_x = sm.ProbPlot(x, fit=True) >>> pp_y = sm.ProbPlot(y, fit=True) >>> fig = pp_x.qqplot(line='45', other=pp_y) >>> plt.show()
The following plot displays some options, follow the link to see the code.
ppplot ([xlabel, ylabel, line, other, ax]) | P-P plot of the percentiles (probabilities) of x versus the probabilities (percetiles) of a distribution. |
probplot ([xlabel, ylabel, line, exceed, ax]) | Probability plot of the unscaled quantiles of x versus the probabilities of a distibution (not to be confused with a P-P plot). |
qqplot ([xlabel, ylabel, line, other, ax]) | Q-Q plot of the quantiles of x versus the quantiles/ppf of a distribution or the quantiles of another ProbPlot instance. |
sample_percentiles () | |
sample_quantiles () | |
sorted_data () | |
theoretical_percentiles () | |
theoretical_quantiles () |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.graphics.gofplots.ProbPlot.html