Comments (1)
Does it still return a result? If so, then this is a duplicate of #25
If it doesn't return a result, then I can't replicate this. I get:
> fit = powerlaw.Fit(discrete=True, data=[1]*1000 + [10]*100 + [100]*10 + [1000])
Calculating best minimal value for power law fit
C:\Users\jeff\Anaconda3\lib\site-packages\powerlaw.py:692: RuntimeWarning: invalid value encountered in true_divide
(Theoretical_CDF * (1 - Theoretical_CDF))
> fit.alpha
2.0547757242410278
from powerlaw.
Related Issues (20)
- `estimate_discrete` should be False by default or raise a warning for x_min < 6 HOT 1
- p_value not computed from normalizes R HOT 6
- Issue with the x_min
- Curve fitted using power law is far from the data points
- Version label
- Added xmin computation does not work for distributions != power_law/truncated_power_law HOT 1
- power law plot showing fit and all data, not just data from xmin HOT 1
- New user: Why the curvature in power_law.plot_ccdf fit? HOT 14
- Defunct scipy import HOT 1
- threshold in powerlaw fit HOT 1
- Remove or make optional xmin fitting print
- Fitting a powerlaw with the xmax parameter HOT 17
- How to improve the efficiency of the fit.
- Get the estimates when i only have an probability distribution from empirical data
- Some issues in lognormal fit
- how to calculate the R value properly for discrete data
- Feature Request: Return the normalization constant HOT 9
- Please remove print statement on line 341 of powerlaw.py
- parameter1 attribute not set for fit.powerlaw HOT 1
- Can not pass 'bins' keyword to `plot_pdf` HOT 2
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from powerlaw.