Description
The Linear Regression (td_lin_reg_mle
) function is composed of the
functions Linear Regression and Linear Regression Internal. Linear
Regression Internal function takes a data set and outputs a linear regression
model. Linear Regression function takes the linear regression model and outputs
its coefficients. One of the output model coefficient corresponds to
the slope intercept. The function ignores input rows with NULL values.
Usage
td_lin_reg_mle ( formula = NULL, data = NULL, data.sequence.column = NULL )
Arguments
formula |
Required Argument. |
data |
Required Argument. |
data.sequence.column |
Optional Argument. |
Value
Function returns an object of class "td_lin_reg_mle" which is a named
list containing Teradata tbl object.
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("linearregression_example", "housing_data") # Create remote tibble objects. housing_data <- tbl(con, "housing_data") # Example 1 - This example uses the Linear Regression function # to find the coefficients of the independent variables that # determine the selling price of a home in a given neighborhood. td_lin_reg_out <- td_lin_reg_mle(data = housing_data, formula = (sellingprice ~ housesize + lotsize + bedrooms + granite + upgradedbathroom) )