sdf_rexp: Generate random samples from an exponential distribution

In sparklyr: R Interface to Apache Spark

Generate random samples from an exponential distribution

Description

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

Usage

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

Arguments

sc	A Spark connection.
n	Sample Size (default: 1000).
rate	Rate of the exponential distribution (default: 1). The exponential distribution with rate lambda has mean 1 / lambda and density f(x) = lambda e ^ - lambda x.
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_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.