### Description

The MovingAverage function calculates the moving average of the
target columns based on the moving average types argument ("mvgtype").

Possible moving average types:

'C' - Cumulative moving average.

'E' - Exponential moving average.

'M' - Modified moving average.

'S' - Simple moving average.

'T' - Triangular moving average.

'W' - Weighted moving average.

Note: This function is only available when tdplyr is connected to Vantage 1.1 or later versions.

### Usage

td_moving_average_sqle ( data = NULL, target.columns = NULL, alpha = 0.1, start.rows = 2, window.size = 10, include.first = FALSE, mavgtype = "C", data.partition.column = NULL, data.order.column = NULL )

### Arguments

`data` |
Required Argument. |

`data.partition.column` |
Required Argument. |

`data.order.column` |
Required Argument. |

`target.columns` |
Optional Argument. |

`alpha` |
Optional Argument. |

`start.rows` |
Optional Argument. |

`window.size` |
Optional Argument. |

`include.first` |
Optional Argument. |

`mavgtype` |
Optional Argument. "S": The MovingAverage function computes the simple moving average of points in a series. "W": The MovingAverage function computes the weighted moving average the average of points in a time series, applying weights to older values. The weights for the older values decrease arithmetically. "E": The MovingAverage function computes the exponential moving average of the points in a time series, exponentially decreasing the weights of older values. "C": The MovingAverage function computes the cumulative moving average of a value from the beginning of a series. "M": The MovingAverage function computes moving average of points in series. "T": The MovingAverage function computes double-smoothed average of points in series.
Default Value: "C" |

### Value

Function returns an object of class "td_moving_average_sqle" 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") loadExampleData("weightedmovavg_example", "stock_vol") # Create object(s) of class "tbl_teradata". ibm_stock <- tbl(con, "ibm_stock") # Example 1: Compute the exponential moving average td_exponential_mov_avg_out <- td_moving_average_sqle(data = ibm_stock, data.partition.column = c("name"), data.order.column = c("period"), target.columns = c("stockprice"), start.rows = 10, include.first = TRUE, mavgtype = "E" ) # Example 2: Compute the cumulative moving average for "stockprice". td_cumulative_mov_avg_out <- td_moving_average_sqle(data = ibm_stock, data.partition.column = c("name"), data.order.column = c("period"), target.columns = c("stockprice"), mavgtype = "C" ) # Example 3: Compute the simple moving average for "stockprice". td_simple_mov_avg_out <- td_moving_average_sqle(data = ibm_stock, data.partition.column = "name", data.order.column = "period", target.columns = "stockprice", include.first = TRUE, window.size = 10, mavgtype = "S" ) # The input table, stock_vol, contains hypothetical stock price and volume data of three # companies between 17 May 1961 and 21 June 1961. stock_vol <- tbl(con, "stock_vol") # Example 4: This example computes the weighted moving average for stockprice and volume # for three companies. td_weighted_mov_avg_out <- td_moving_average_sqle(data = stock_vol, data.partition.column = c("id"), data.order.column = c("name"), target.columns = c("stockprice","volume"), include.first = TRUE, window.size = 5, mavgtype = "W" ) # Example 5: Triangular Moving Average td_triangular_mov_avg_out <- td_moving_average_sqle(data = stock_vol, data.partition.column = "name", data.order.column = "period", target.columns = c("stockprice"), include.first = TRUE, window.size = 3, mavgtype = "T" ) # Example 6: Modified Moving Average. td_modified_mov_avg_out <- td_moving_average_sqle(data = stock_vol, data.partition.column = "name", data.order.column = "period", target.columns = c("stockprice"), include.first = TRUE, window.size = 3, mavgtype = "M" )