| sdf_rbinom {sparklyr} | R Documentation |
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
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()
[Package sparklyr version 1.8.6 Index]