sdf_rbinom
Generate random samples from a binomial distribution
Description
Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a binomial distribution.
Usage
sdf_rbinom(
sc,
n,
size,
prob,
num_partitions = NULL,
seed = NULL,
output_col = "x"
)
Arguments
Argument | Description |
---|---|
sc | A Spark connection. |
n | Sample Size (default: 1000). |
size | Number of trials (zero or more). |
prob | Probability of success on each trial. |
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_rcauchy()
, sdf_rchisq()
, sdf_rexp()
, sdf_rgamma()
, sdf_rgeom()
, sdf_rhyper()
, sdf_rlnorm()
, sdf_rnorm()
, sdf_rpois()
, sdf_rt()
, sdf_runif()
, sdf_rweibull()