| sdf_rexp {sparklyr} | R Documentation |
Generate random samples from an exponential distribution
Description
Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from an exponential distribution.
Usage
sdf_rexp(sc, n, rate = 1, num_partitions = NULL, seed = NULL, output_col = "x")
Arguments
sc |
A Spark connection. |
n |
Sample Size (default: 1000). |
rate |
Rate of the exponential distribution (default: 1). The exponential distribution with rate lambda has mean 1 / lambda and density f(x) = lambda e ^ - lambda x. |
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_rgamma(),
sdf_rgeom(),
sdf_rhyper(),
sdf_rlnorm(),
sdf_rnorm(),
sdf_rpois(),
sdf_rt(),
sdf_runif(),
sdf_rweibull()