Generate random samples from a Gamma distribution
R/sdf_stat.R
sdf_rgamma
Description
Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a Gamma distribution.
Usage
sdf_rgamma(
sc,
n,
shape, rate = 1,
num_partitions = NULL,
seed = NULL,
output_col = "x"
)
Arguments
Arguments | Description |
---|---|
sc | A Spark connection. |
n | Sample Size (default: 1000). |
shape | Shape parameter (greater than 0) for the Gamma distribution. |
rate | Rate parameter (greater than 0) for the Gamma distribution (scale is 1/rate). |
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_rexp()
, sdf_rgeom()
, sdf_rhyper()
, sdf_rlnorm()
, sdf_rnorm()
, sdf_rpois()
, sdf_rt()
, sdf_runif()
, sdf_rweibull()