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fit_exponential(vals,
thresh)
Maximum likelihood fit for the coefficient alpha for a distribution
of discrete values p(x) = alpha exp(-alpha (x-x_t)) above a threshold
x_t. |
source code
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fit_rayleigh(vals,
thresh)
Maximum likelihood fit for the coefficient alpha for a distribution
of discrete values p(x) = alpha x exp(-alpha (x**2-x_t**2)/2) above a
threshold x_t. |
source code
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fit_power(vals,
thresh)
Maximum likelihood fit for the coefficient alpha for a distribution
of discrete values p(x) = ((alpha-1)/x_t) (x/x_t)**-alpha above a
threshold x_t. |
source code
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expfit(xvals,
alpha,
thresh)
The fitted exponential function normalized to 1 above threshold |
source code
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expfit_cum(xvals,
alpha,
thresh)
The integral of the exponential fit above a given value (reverse CDF)
normalized to 1 above threshold |
source code
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rayleighfit_cum(xvals,
alpha,
thresh)
The integral of the Rayleigh fit above the x-values given (reverse
CDF) normalized to 1 above threshold |
source code
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powerfit(xvals,
alpha,
thresh)
The fitted power-law function normalized to 1 above threshold |
source code
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powerfit_cum(xvals,
alpha,
thresh)
The integral of the power-law fit above the x-values given (reverse
CDF) normalized to 1 above threshold |
source code
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fit_above_thresh(distr,
vals,
thresh=None)
Maximum likelihood fit for the coefficient alpha for a distribution
of discrete values p(x) = alpha exp(-alpha*x) above a given
threshold. |
source code
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tail_threshold(vals,
N=1000)
Determine a threshold above which there are N louder values |
source code
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fit_fn(distr,
xvals,
alpha,
thresh)
The fitted function normalized to 1 above threshold |
source code
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cum_fit(distr,
xvals,
alpha,
thresh)
The integral of the fitted function above a given value (reverse CDF)
normalized to 1 above threshold |
source code
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KS_test(distr,
vals,
alpha,
thresh=None)
Perform Kolmogorov-Smirnov test of the given set of discrete values
above a given threshold for the fitted distribution function ex.:
KS_test('exponential', vals, alpha, thresh) If no threshold is
specified, the minimum sample value will be used. |
source code
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