statsmodels.nonparametric.kde.KDEUnivariate¶
- class statsmodels.nonparametric.kde.KDEUnivariate(endog)[source]¶
Univariate Kernel Density Estimator.
- Parameters:
- endogarray_like
The variable for which the density estimate is desired.
See also
KDEMultivariate
kdensity
,kdensityfft
Notes
If cdf, sf, cumhazard, or entropy are computed, they are computed based on the definition of the kernel rather than the FFT approximation, even if the density is fit with FFT = True.
KDEUnivariate is much faster than KDEMultivariate, due to its FFT-based implementation. It should be preferred for univariate, continuous data. KDEMultivariate also supports mixed data.
Examples
>>> import statsmodels.api as sm >>> import matplotlib.pyplot as plt
>>> nobs = 300 >>> np.random.seed(1234) # Seed random generator >>> dens = sm.nonparametric.KDEUnivariate(np.random.normal(size=nobs)) >>> dens.fit() >>> plt.plot(dens.cdf) >>> plt.show()
- Attributes:
- cdf
Returns the cumulative distribution function evaluated at the support.
Will not work if fit has not been called.
- cumhazard
Returns the hazard function evaluated at the support.
Will not work if fit has not been called.
- entropy
Returns the differential entropy evaluated at the support
Will not work if fit has not been called. 1e-12 is added to each probability to ensure that log(0) is not called.
- icdf
Inverse Cumulative Distribution (Quantile) Function
Will not work if fit has not been called. Uses scipy.stats.mstats.mquantiles.
- sf
Returns the survival function evaluated at the support.
Will not work if fit has not been called.
Methods
evaluate
(point)Evaluate density at a point or points.
fit
([kernel, bw, fft, weights, gridsize, ...])Attach the density estimate to the KDEUnivariate class.
Properties
Returns the cumulative distribution function evaluated at the support.
Returns the hazard function evaluated at the support.
Returns the differential entropy evaluated at the support
Inverse Cumulative Distribution (Quantile) Function
Returns the survival function evaluated at the support.