Description
The ExponentialMovAvg function computes the exponential moving average
of points in a time series, exponentially decreasing the
weights of older values.
Usage
td_exponential_mov_avg_mle (
data = NULL,
target.columns = NULL,
alpha = 0.1,
start.rows = 2,
include.first = FALSE,
data.sequence.column = NULL,
data.partition.column = NULL,
data.order.column = NULL
)
Arguments
data 
Required Argument.
Specifies the name of the tbl_teradata that contains the columns.

data.partition.column 
Required Argument.
Specifies Partition By columns for "data".
Values to this argument can be provided as a vector, if multiple
columns are used for partition.
Types: character OR vector of Strings (character)

data.order.column 
Required Argument.
Specifies Order By columns for "data".
Values to this argument can be provided as a vector, if multiple
columns are used for ordering.
Types: character OR vector of Strings (character)

target.columns 
Optional Argument.
Specifies the input column names for which the moving average is to
be computed. If you omit this argument, then the function copies
every input column to the output tbl_teradata but does not compute
moving average.
Types: character OR vector of Strings (character)

alpha 
Optional Argument.
Specifies the damping factor, a value in the range [0, 1], which
represents a percentage in the range [0, 100]. For example, if alpha
is 0.2, then the damping factor is 20
older observations faster.
Default Value: 0.1
Types: numeric

start.rows 
Optional Argument.
Specifies the number of rows at the beginning of the time series that
the function skips before it begins the calculation of the
exponential moving average. The function uses the arithmetic average
of these rows as the initial value of the exponential moving average.
Default Value: 2
Types: integer

include.first 
Optional Argument.
Specifies whether to include the starting rows in the output tbl_teradata.
If you specify TRUE, the output columns for the starting rows
contain NA, because their exponential moving average is undefined.
Default Value: FALSE
Types: logical

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)

Value
Function returns an object of class "td_exponential_mov_avg_mle"
which is a named list containing object of class "tbl_teradata".
Named list member can be referenced directly with the "$" operator
using name: result.
Examples
# Get the current context/connection
con < td_get_context()$connection
# Load example data.
loadExampleData("exponentialmovavg_example", "ibm_stock")
# Create object(s) of class "tbl_teradata".
ibm_stock < tbl(con, "ibm_stock")
# Example  Compute the exponential moving average
td_exponential_mov_avg_out < td_exponential_mov_avg_mle(data = ibm_stock,
data.partition.column = c("name"),
data.order.column = c("period"),
target.columns = c("stockprice"),
start.rows = 10,
include.first = TRUE
)