A Set of Statistical Functions

mlpy.bootstrap_ci(x, B=1000, alpha=0.050000000000000003, seed=0)

Computes the (1-alpha) Bootstrap confidence interval from empirical bootstrap distribution of sample mean.

The lower and upper confidence bounds are the (B*alpha/2)-th and B * (1-alpha/2)-th ordered means, respectively. For B = 1000 and alpha = 0.05 these are the 25th and 975th ordered means.

mlpy.quantile(x, f)

Returns a quantile value of x.

The quantile is determined by the f, a fraction between 0 and 1. For example, to compute the value of the 75th percentile f should have the value 0.75.

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Canberra Distances and Stability Indicator of Ranked Lists

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