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RandomMonomialIdeals :: sample

sample -- generates a sample from the given model

Synopsis

Usage:

sample(Model,ZZ)
Inputs:
- M, an instance of the type Model, to be sampled from
- N, an integer, sample size
Outputs:
- an instance of the type Sample, a sample of size $N$ from the given model $M$

Description

This function generates $N$ realizations of the random variable that has the distribution specified by the given model.

i1 : s=sample(ER(3,2,0.2),4)

o1 = Sample{...4...}

o1 : Sample

One obtains the data from the object of type Sample (that is, the actual sample in the statistical sense) as follows:

i2 : getData s

                2                       2   2
o2 = {{x x }, {x , x x }, {x , x x }, {x , x }}
        1 2     1   2 3     2   1 3     1   2

o2 : List

The actual sample contains more information than just the data itself:

i3 : peek s

o3 = Sample{ModelName => Erdos-Renyi                          }
            Parameters => (3, 2, .2)
            SampleSize => 4
                               2                       2   2
            Data => {{x x }, {x , x x }, {x , x x }, {x , x }}
                       1 2     1   2 3     2   1 3     1   2

and one can easily obtain sample statistics:

i4 : statistics(s,degree@@ideal)

o4 = HashTable{Histogram => Tally{2 => 2}}
                                  4 => 2
               Mean => 3
               StdDev => 1

o4 : HashTable

See also

statistics -- generate statistics for a sample
getData -- get the underlying samples

Ways to use `sample` :

"sample(Model,ZZ)"
sample(String) -- creates an object of type Sample from a sample stored in a directory on disk

For the programmer

The object sample is a method function.