# LinRegIntercept (PEL)

This function calculates the linear regression of a set and returns the value of the x-intercept in the regression line `y = ax + b`

.

```
LinRegIntercept(
Scope_Expression,
Numeric_Expression_y
[ , Numeric_Expression_x ]
)
```

#### Parameters

- Scope_Expression

A valid PerformancePoint Expression Language (PEL) expression that returns a set.

- Numeric_Expression_y

A valid numeric expression that is typically a PEL expression of cell coordinates that return a number that represents values for the y-axis.

- Numeric_Expression_x

A valid numeric expression that is typically a PEL expression of cell coordinates that return a number that represents values for the x-axis.

## Return Value

After obtaining the set of points, the **LinRegIntercept** function returns the intercept of the regression line (b in the equation` y = ax + b`

).

## Remarks

Linear regression uses the least-squares method to calculate 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, *Numeric_Expression_y*,**to obtain the values for the y-axis. The function then evaluates the specified set against the second numeric expression, *Numeric_Expression_x*, if specified, to obtain the values for the x-axis.

If *Numeric_Expression_x* 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 x-axis argument is frequently used with the Time dimension.

To determine the slope of the regression line `y = ax+b`

, use LinRegSlope (PEL).

The PEL compiler cannot generate SQL code for this function.