sdf_rgamma: Generate random samples from a Gamma distribution

In sparklyr: R Interface to Apache Spark

Generate random samples from a Gamma distribution

Description

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

Usage

sdf_rgamma(
  sc,
  n,
  shape,
  rate = 1,
  num_partitions = NULL,
  seed = NULL,
  output_col = "x"
)

Arguments

sc	A Spark connection.
n	Sample Size (default: 1000).
shape	Shape parameter (greater than 0) for the Gamma distribution.
rate	Rate parameter (greater than 0) for the Gamma distribution (scale is 1/rate).
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_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.