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The Discrete uniform distribution is a discrete probablity distribution where a finite number of values are equally likely to occur. The values are 1,2,3,...,n.
For example throwing a fair die of 6 sides numbered 1 through 6 follows a \({\it DiscreteUniform}(1/6)\) distribution.
Returns the value at x of the probability function of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The pdf is $$ f(x,n) = {1\over n} $$
Returns the value at x of the distribution function of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The cdf is $$ F(x; n) = {\lfloor x \rfloor \over n} $$
Returns the q-quantile of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer; in other words, this is the inverse of cdf_discrete_uniform. Argument q must be an element of [0,1]. To make use of this function, write first load("distrib").
Returns the mean of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The mean is $$ E[X] = {n+1\over 2} $$
Returns the variance of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The variance is $$ V[X] = {n^2-1 \over 12} $$
Returns the standard deviation of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The standard deviation is $$ D[X] = {\sqrt{n^2-1} \over 2\sqrt{3}} $$
Returns the skewness coefficient of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The skewness coefficient is $$ SK[X] = 0 $$
Returns the kurtosis coefficient of a
\({\it DiscreteUniform}(n)\) random variable, with n a strictly positive integer. To make use of this function, write first load("distrib").
The kurtosis coefficient is $$ KU[X] = - {6(n^2+1)\over 5 (n^2-1)} $$
Returns a
\({\it DiscreteUniform}(n)\) random variate, with n a strictly positive integer. Calling random_discrete_uniform with a second argument m, a random sample of size m will be simulated.
This is a direct application of the random built-in Maxima function.
See also random. To make use of this function, write first load("distrib").