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

and one can easily obtain sample statistics:

i4 : statistics(s,degree@@ideal)

o4 = HashTable{Histogram => Tally{2 => 4}}
               Mean => 2
               StdDev => 0

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.