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sparklyr (version 1.8.5)

sdf_rchisq: Generate random samples from a chi-squared distribution

Description

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

Usage

sdf_rchisq(sc, n, df, num_partitions = NULL, seed = NULL, output_col = "x")

Arguments

sc

A Spark connection.

n

Sample Size (default: 1000).

df

Degrees of freedom (non-negative, but can be non-integer).

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_rexp(), sdf_rgamma(), sdf_rgeom(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_rt(), sdf_runif(), sdf_rweibull()