Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

cauchy distribution python | 1.06 | 0.3 | 8091 | 11 | 26 |

cauchy | 1.55 | 0.6 | 3577 | 21 | 6 |

distribution | 1.08 | 1 | 3238 | 16 | 12 |

python | 1.09 | 0.3 | 5895 | 6 | 6 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

cauchy distribution python | 0.08 | 0.8 | 3158 | 34 |

cauchy distribution in python | 0.45 | 0.1 | 1421 | 30 |

standard cauchy distribution python | 0.35 | 0.9 | 1336 | 60 |

and the Standard Cauchy distribution just sets x 0 = 0 and γ = 1 The Cauchy distribution arises in the solution to the driven harmonic oscillator problem, and also describes spectral line broadening. It also describes the distribution of values at which a line tilted at a random angle will cut the x axis.

Specifically, cauchy.pdf (x, loc, scale) is identically equivalent to cauchy.pdf (y) / scale with y = (x - loc) / scale. Note that shifting the location of a distribution does not make it a “noncentral” distribution; noncentral generalizations of some distributions are available in separate classes.

scipy.stats.cauchy = <scipy.stats._continuous_distns.cauchy_gen object> [source] ¶ A Cauchy continuous random variable. As an instance of the rv_continuous class, cauchy object inherits from it a collection of generic methods (see below for the full list), and completes them with details specific for this particular distribution.

The derivative of the quantile function, the quantile density function, for the Cauchy distribution is: Q ′ ( p ; γ ) = γ π sec 2 [ π ( p − 1 2 ) ] . {\displaystyle Q' (p;\gamma )=\gamma \,\pi \, {\sec }^ {2}\left [\pi \left (p- { frac {1} {2}}ight)ight].\!}