Updated: March 2, 2016
Calculates the linear regression of a set and returns the value of the x-intercept in the regression line, y = ax + b.
LinRegIntercept(Set_Expression, Numeric_Expression_y [ ,Numeric_Expression_x ] )
A valid Multidimensional Expressions (MDX) expression that returns a set.
A valid numeric expression that is typically a Multidimensional Expressions (MDX) expression of cell coordinates that return a number that represents values for the y-axis.
A valid numeric expression that is typically a Multidimensional Expressions (MDX) expression of cell coordinates that return a number that represents values for the x-axis.
Linear regression, that uses the least-squares method, calculates the equation of a regression line (that is, the best-fit line for a series of points). The regression line has the following equation, where a is the slope and b is the intercept:
y = ax+b
The LinRegIntercept function evaluates the specified set against the first numeric expression to obtain the values for the y-axis. The function then evaluates the specified set against the second numeric expression, if specified, to obtain the values for the x-axis. If the second numeric expression is not specified, the function uses the current context of the cells in the specified set as values for the x-axis. Not specifying the the x-axis argument is frequently used with the Time dimension.
After obtaining the set of points, the LinRegIntercept function returns the intercept of the regression line (b in the previous equation).
The following example returns the intercept of a regression line for the unit sales and the store sales measures.
LinRegIntercept(LastPeriods(10),[Measures].[Unit Sales],[Measures].[Store Sales])