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- numpy.random.Generator.beta
...e structure Random sampling (numpy.random) Random Generator numpy.random.Generator.beta...
- numpy.random.Generator.beta (Python method, in numpy.random.Generator.beta)
- NumPy 1.16.4 Release Notes
...to bugs in the application of log to random floating point numbers, the stream may change when sampling from np.random.beta, np.random.binomial, np.random.laplace, np.random.logistic, np.random.logseries or np.random.multinomial if a 0 is...
- NumPy 1.17.0 Release Notes
...module Due to bugs in the application of log to random floating point numbers, the stream may change when sampling from beta, binomial, laplace, logistic, logseries or multinomial if a 0 is generated in the underlying MT19937 random stream....
- numpy.random.beta
...ule structure Random sampling (numpy.random) Legacy random generation numpy.random.beta...
- numpy.random.dirichlet
...rom a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference....
- numpy.random.exponential
...le=1.0, size=None) Draw samples from an exponential distribution. Its probability density function is \[f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}),\] for x > 0 and 0 elsewhere. \(\beta\) is the scale parameter, which is...
- numpy.random.Generator.beta
...e structure Random sampling (numpy.random) Random Generator numpy.random.Generator.beta...
- numpy.random.Generator.dirichlet
...rom a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference....
- numpy.random.Generator.exponential
...le=1.0, size=None) Draw samples from an exponential distribution. Its probability density function is \[f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}),\] for x > 0 and 0 elsewhere. \(\beta\) is the scale parameter, which is...
- numpy.random.Generator.gumbel
...s with “exponential-like” tails. The probability density for the Gumbel distribution is \[p(x) = \frac{e^{-(x - \mu)/ \beta}}{\beta} e^{ -e^{-(x - \mu)/ \beta}},\] where \(\mu\) is the mode, a location parameter, and \(\beta\) is the scale...
- numpy.random.Generator.power
...ower function distribution is just the inverse of the Pareto distribution. It may also be seen as a special case of the Beta distribution. It is used, for example, in modeling the over-reporting of insurance claims. References [1] Christi...
- numpy.random.gumbel
...s with “exponential-like” tails. The probability density for the Gumbel distribution is \[p(x) = \frac{e^{-(x - \mu)/ \beta}}{\beta} e^{ -e^{-(x - \mu)/ \beta}},\] where \(\mu\) is the mode, a location parameter, and \(\beta\) is the scale...
- numpy.random.power
...ower function distribution is just the inverse of the Pareto distribution. It may also be seen as a special case of the Beta distribution. It is used, for example, in modeling the over-reporting of insurance claims. References [1] Christi...
- numpy.random.RandomState.beta
...e Random sampling (numpy.random) Legacy random generation numpy.random.RandomState.beta...
- numpy.random.RandomState.dirichlet
...rom a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference....
- numpy.random.RandomState.exponential
...le=1.0, size=None) Draw samples from an exponential distribution. Its probability density function is \[f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}),\] for x > 0 and 0 elsewhere. \(\beta\) is the scale parameter, which is...
- numpy.random.RandomState.gumbel
...s with “exponential-like” tails. The probability density for the Gumbel distribution is \[p(x) = \frac{e^{-(x - \mu)/ \beta}}{\beta} e^{ -e^{-(x - \mu)/ \beta}},\] where \(\mu\) is the mode, a location parameter, and \(\beta\) is the scale...
- numpy.random.RandomState.power
...ower function distribution is just the inverse of the Pareto distribution. It may also be seen as a special case of the Beta distribution. It is used, for example, in modeling the over-reporting of insurance claims. References [1] Christi...