Description
The Arima function calculates the coefficients for a sequence of
parameters, producing an ARIMA model that is typically input to the
ArimaPredictor (td_arima_predict_mle
) function.
Usage
td_arima_mle (
data = NULL,
orders.table = NULL,
timestamp.columns = NULL,
value.column = NULL,
orders = NULL,
seasonal = NULL,
period = NULL,
include.mean = FALSE,
partition.columns = NULL,
max.iterations = 10000,
method = "SSE",
include.drift = FALSE,
order.p = NULL,
order.d = NULL,
order.q = NULL,
seasonal.order.p = NULL,
seasonal.order.d = NULL,
seasonal.order.q = NULL,
data.sequence.column = NULL,
orders.table.sequence.column = NULL
)
Arguments
data |
Required Argument. |
orders.table |
Optional Argument. |
timestamp.columns |
Required Argument. |
value.column |
Required Argument. |
orders |
Optional Argument. |
seasonal |
Optional Argument. |
period |
Optional Argument. |
include.mean |
Optional Argument. |
partition.columns |
Optional Argument. |
max.iterations |
Optional Argument. |
method |
Optional Argument.
Default Value: "SSE" |
include.drift |
Optional Argument. |
order.p |
Optional Argument. |
order.d |
Optional Argument. |
order.q |
Optional Argument. |
seasonal.order.p |
Optional Argument. |
seasonal.order.d |
Optional Argument. |
seasonal.order.q |
Optional Argument. |
data.sequence.column |
Optional Argument. |
orders.table.sequence.column |
Optional Argument. |
Value
Function returns an object of class "td_arima_mle" which is a named
list containing objects of class "tbl_teradata".
Named list members can be referenced directly with the "$" operator
using the following names:
coefficient
-
residual.table
output
Examples
# Get the current context/connection
con <- td_get_context()$connection
# Load example data.
loadExampleData("arima_example", "milk_timeseries")
# Create object(s) of class "tbl_teradata".
milk_timeseries <- tbl(con, "milk_timeseries")
# Example 1: Generate Arima model using only orders paremeter without
# "partition.columns" and seasonal parameters.
td_arima_out <- td_arima_mle(data = milk_timeseries,
timestamp.columns = c("period"),
value.column = "milkpound",
orders = "0,1,2",
include.drift=TRUE)
# Example 2: Generate Arima model using seasonal orders parameter.
td_arima_out <- td_arima_mle(data = milk_timeseries,
timestamp.columns = c("period"),
value.column = "milkpound",
orders = "0,1,2",
seasonal.order.p = 0,
seasonal.order.d = 1,
seasonal.order.q = 1,
period = 12)