sparklyr (version 1.7.1)

sdf_rbeta: Generate random samples from a Beta distribution

Description

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

Usage

sdf_rbeta(
  sc,
  n,
  shape1,
  shape2,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)

Arguments

sc

A Spark connection.

n

Sample Size (default: 1000).

shape1

Non-negative parameter (alpha) of the Beta distribution.

shape2

Non-negative parameter (beta) of the Beta distribution.

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_rbinom(), sdf_rcauchy(), sdf_rchisq(), sdf_rexp(), sdf_rgamma(), sdf_rgeom(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()