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.
Specifies the name of the tbl_teradata that contains the
input parameters.

orders.table 
Optional Argument.
Specifies the name of the orders tbl_teradata that is generated by
TimeSeriesOrders function.

timestamp.columns 
Required Argument.
Specifies the names of the columns in "data" tbl_teradata that specify the
sequence (time points) of the input parameters. The sequence must
have uniform intervals.
Types: character OR vector of Strings (character)

value.column 
Required Argument.
Specifies the name of the column that contains the time series data
in input tbl_teradata.
Types: character

orders 
Optional Argument.
Specifies the comma separated string of integers values of
the nonseasonal orders p, d, and q for the ARIMA model.
The p and q must be an integer between 0 and 10, inclusive.
The d must be between 0 and 1, inclusive.
Types: character

seasonal 
Optional Argument.
Specifies the comma separated string of integers values of
the seasonal orders sp, sd, and sq for the ARIMA model.
The sp and sq must be an integer between 0 and 10, inclusive.
The sd must be between 0 and 3, inclusive
Types: character

period 
Optional Argument.
Specifies the period of a season (m in the formula). This value must
be a positive integer value. If you specify seasonal, then you must
also specify period.
Types: integer

include.mean 
Optional Argument.
Specifies whether the function adds the mean value (c in the formula)
to the arima model.
Note: If "include.mean" is TRUE, then both d in orders and sd in seasonal
must be 0.
Default Value: FALSE
Types: logical

partition.columns 
Optional Argument.
Specifies the partition columns that will be passed to the output. If
not specified, the output will not contain partition columns.
Types: character OR vector of Strings (character)

max.iterations 
Optional Argument.
Specifies the maximum iteration number for estimating the parameters.
This value must be a positive integer.
Default Value: 10000
Types: integer

method 
Optional Argument.
Specifies the method for fitting the model parameters:
SSE: Sum of squared error.
ML: Maximum likelihood.
Default Value: "SSE"
Permitted Values: SSE, ML
Types: character

include.drift 
Optional Argument.
Specifies whether drift term is included in the ARIMA model.
Note: This argument can only be TRUE when d is nonzero and less than 2.
Default Value: FALSE
Types: logical

order.p 
Optional Argument.
Specifies the p value of the nonseasonal order parameter. The p value must be
an integer between 0 and 10, inclusive.
Types: integer

order.d 
Optional Argument.
Specifies the d value of the nonseasonal order parameter. The d value must be
an integer between 0 and 1, inclusive.
Types: integer

order.q 
Optional Argument.
Specifies the q value of the nonseasonal order parameter. The q value must be
an integer between 0 and 10, inclusive.
Types: integer

seasonal.order.p 
Optional Argument.
Specifies the sp value of the seasonal order parameter. The sp value must be an
integer between 0 and 10, inclusive.
Types: integer

seasonal.order.d 
Optional Argument.
Specifies the sd value of the seasonal order parameter. The sd value must be an
integer between 0 and 3, inclusive.
Types: integer

seasonal.order.q 
Optional Argument.
Specifies the sq value of the seasonal order parameter. The sq value must be an
integer between 0 and 10, inclusive.
Types: integer

data.sequence.column 
Optional Argument.
Specifies the vector of column(s) that uniquely identifies each row
of the input argument "data". The argument is used to ensure
deterministic results for functions which produce results that vary
from run to run.
Types: character OR vector of Strings (character)

orders.table.sequence.column 
Optional Argument.
Specifies the vector of column(s) that uniquely identifies each row
of the input argument "orders.table". The argument is used to ensure
deterministic results for functions which produce results that vary
from run to run.
Types: character OR vector of Strings (character)

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)