sdf_rexp: Generate random samples from an exponential distribution

sdf_rexpR Documentation

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.