sdf_rgeom: Generate random samples from a geometric distribution

sdf_rgeomR Documentation

Generate random samples from a geometric distribution

Description

Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a geometric distribution.

Usage

sdf_rgeom(sc, n, prob, num_partitions = NULL, seed = NULL, output_col = "x")

Arguments

sc

A Spark connection.

n

Sample Size (default: 1000).

prob

Probability of success in each trial.

num_partitions

Number of partitions in the resulting Spark dataframe (default: default parallelism of the Spark cluster).

seed

Random seed (default: a random long integer).

output_col

Name of the output column containing sample values (default: "x").

See Also

Other Spark statistical routines: sdf_rbeta(), sdf_rbinom(), sdf_rcauchy(), sdf_rchisq(), sdf_rexp(), sdf_rgamma(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()


sparklyr documentation built on May 29, 2024, 2:58 a.m.