radom radom模块提供了随机生成对象的方法 Help on module random: NAME random - Random variable generators. FILE /usr/local/lib/python2.7/random.py MODULE DOCS http://docs.python.org/library/random DESCRIPTION integers -------- uniform within range sequences --------
Random - Generate pseudo-random numbers Source code: Lib/random.py This module implements pseudo-random number generators for various distributions. For integers, uniform selection from a range. For sequences, uniform selection of a random element, a
As an example of subclassing, the random module provides the WichmannHill class that implements an alternative generator in pure Python. The class provides a backward compatible way to reproduce results from earlier versions of Python, which used the
Computational Methods in Bayesian Analysis Computational Methods in Bayesian Analysis [Markov chain Monte Carlo][Gibbs Sampling][The Metropolis-Hastings Algorithm][Random-walk Metropolis-Hastings][Adaptive Metropolis] About the author This noteboo
akka-stream的数据流可以由一些组件组合而成.这些组件统称数据流图Graph,它描述了数据流向和处理环节.Source,Flow,Sink是最基础的Graph.用基础Graph又可以组合更复杂的复合Graph.如果一个Graph的所有端口(输入.输出)都是连接的话就是一个闭合流图RunnableGraph,否则就属于·开放流图PartialGraph.一个完整的(可运算的)数据流就是一个RunnableGraph.Graph的输出出入端口可以用Shape来描述: /** * A Shap
http://blog.csdn.net/pipisorry/article/details/49515215 统计函数Statistical functions(scipy.stats) Python有一个很好的统计推断包.那就是scipy里面的stats. Scipy的stats模块包含了多种概率分布的随机变量,随机变量分为连续的和离散的两种.所有的连续随机变量都是rv_continuous的派生类的对象,而所有的离散随机变量都是 rv_discrete的派生类的对象. This modul
一.garchFit函数的参数--------------------------------------------- algorithm a string parameter that determines the algorithm used for maximum likelihood estimation. 设定最大似然估计所用的算法 cond.dist a character string naming the desired conditional distribution. Va
scipy.stats Scipy的stats模块包含了多种概率分布的随机变量,随机变量分为连续的和离散的两种.所有的连续随机变量都是rv_continuous的派生类的对象,而所有的离散随机变量都是 rv_discrete的派生类的对象. This module contains a large number of probability distributions as well as a growing library of statistical functions. Each univ
"""Random variable generators. integers -------- uniform within range sequences --------- pick random element pick random sample pick weighted random sample generate random permutation distributions on the real line: -----------------------
