Description
The CCMPrepare function prepares an input tbl_teradata for the CCM
function by adding a partition column, "ccm_id", and partitioning
the data. Using the CCMPrepare function is optional. However,
partitioning the data, instead of having all sequences on one
vworker, may increase the speed of the CCM (td_ccm_mle
)
function for large data sets consisting of multiple sequences.
Usage
td_ccm_prepare_mle ( data = NULL, data.partition.column = "1", data.order.column = NULL )
Arguments
data |
Required Argument. |
data.partition.column |
Optional Argument |
data.order.column |
Optional Argument. |
Value
Function returns an object of class "td_ccm_prepare_mle" which is a
named list containing object of class "tbl_teradata".
Named list member can be referenced directly with the "$" operator
using the name: result.
Examples
# Get the current context/connection con <- td_get_context()$connection # Load example data. loadExampleData("ccmprepare_example", "ccmprepare_input") # The ccmprepare_input tbl_teradata is a collection of nine # time series consisting of 10 values for each of three variables # (expenditure, income, and investment). ccmprepare_input <- tbl(con, "ccmprepare_input") # Prepare the given input for CCM. td_ccm_prepare_out <- td_ccm_prepare_mle(data = ccmprepare_input, data.partition.column = "id" )