sdf_rt
Generate random samples from a t-distribution
Description
Generator method for creating a single-column Spark dataframes comprised of i.i.d. samples from a t-distribution.
Usage
sdf_rt(sc, n, df, num_partitions = NULL, seed = NULL, output_col = "x")Arguments
| Argument | Description |
|---|---|
| sc | A Spark connection. |
| n | Sample Size (default: 1000). |
| df | Degrees of freedom (> 0, maybe non-integer). |
| 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_rgamma(), sdf_rgeom(), sdf_rhyper(), sdf_rlnorm(), sdf_rnorm(), sdf_rpois(), sdf_runif(), sdf_rweibull()