sdf_rcauchy {sparklyr} | R Documentation |
Generate random samples from a Cauchy distribution
Description
Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a Cauchy distribution.
Usage
sdf_rcauchy(
sc,
n,
location = 0,
scale = 1,
num_partitions = NULL,
seed = NULL,
output_col = "x"
)
Arguments
sc |
A Spark connection. |
n |
Sample Size (default: 1000). |
location |
Location parameter of the distribution. |
scale |
Scale parameter of the distribution. |
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_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]