A uniform discrete random variable.
Discrete random variables are defined from a standard form and may require some shape parameters to complete its specification. Any optional keyword parameters can be passed to the methods of the RV object as given below:
Parameters : | x : array_like
q : array_like
min, max : array_like
loc : array_like, optional
scale : array_like, optional
size : int or tuple of ints, optional
moments : str, optional
Alternatively, the object may be called (as a function) to fix the shape and : location parameters returning a “frozen” discrete RV object: : rv = randint(min, max, loc=0) :
|
---|
Notes
The probability mass function for randint is:
randint.pmf(k) = 1./(max- min)
for k = min,...,max.
randint takes min and max as shape parameters.
Examples
>>> from scipy.stats import randint
>>> [ min, max ] = [<Replace with reasonable values>]
>>> rv = randint(min, max)
Display frozen pmf
>>> x = np.arange(0, np.minimum(rv.dist.b, 3))
>>> h = plt.vlines(x, 0, rv.pmf(x), lw=2)
Here, rv.dist.b is the right endpoint of the support of rv.dist.
Check accuracy of cdf and ppf
>>> prb = randint.cdf(x, min, max)
>>> h = plt.semilogy(np.abs(x - randint.ppf(prb, min, max)) + 1e-20)
Random number generation
>>> R = randint.rvs(min, max, size=100)
Methods
rvs(min, max, loc=0, size=1) | Random variates. |
pmf(x, min, max, loc=0) | Probability mass function. |
logpmf(x, min, max, loc=0) | Log of the probability mass function. |
cdf(x, min, max, loc=0) | Cumulative density function. |
logcdf(x, min, max, loc=0) | Log of the cumulative density function. |
sf(x, min, max, loc=0) | Survival function (1-cdf — sometimes more accurate). |
logsf(x, min, max, loc=0) | Log of the survival function. |
ppf(q, min, max, loc=0) | Percent point function (inverse of cdf — percentiles). |
isf(q, min, max, loc=0) | Inverse survival function (inverse of sf). |
stats(min, max, loc=0, moments=’mv’) | Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). |
entropy(min, max, loc=0) | (Differential) entropy of the RV. |
expect(func, min, max, loc=0, lb=None, ub=None, conditional=False) | Expected value of a function (of one argument) with respect to the distribution. |
median(min, max, loc=0) | Median of the distribution. |
mean(min, max, loc=0) | Mean of the distribution. |
var(min, max, loc=0) | Variance of the distribution. |
std(min, max, loc=0) | Standard deviation of the distribution. |
interval(alpha, min, max, loc=0) | Endpoints of the range that contains alpha percent of the distribution |