sdf_rbeta: Generate random samples from a Beta distribution

In sparklyr: R Interface to Apache Spark

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()

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