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# Second simulated data for the simple linear regression model

`SLM2.Rd`

Second data used in example 4 of Salmerón, García and García (2024) (subsection 4.4) on the special case of the simple linear model.

## Usage

    data("SLM2")

## Format

A data frame with 50 observations on the following 3 variables:

`y2`

  Dependent variable simulated as y = 3 + 4*Z + u where u is normally distributed with a mean of 0 and a variance of 2.

`cte`

  Intercept.

`Z`

  Simulated from a normal distribution with a mean of 10 and a variance of 0.1.

## References

Salmerón, R., García, C.B. and García, J. (2025). A redefined Variance Inflation Factor: overcoming the limitations of the Variance Inflation Factor. Computational Economics, 65, 337-363, doi: https://doi.org/10.1007/s10614-024-10575-8.

## Examples

      head(SLM2, n=5)
    #>         y2 cte         Z
    #> 1 43.01204   1  9.978211
    #> 2 40.04163   1  9.878235
    #> 3 40.17086   1  9.924592
    #> 4 40.79076   1 10.019123
    #> 5 44.72774   1 10.104728
      y = SLM2[,1]
      x = SLM2[,2:3]
      multicollinearity(y, x)
    #>        RVIFs         c0         c3 Scenario Affects
    #> 1 187.800878 21.4798003 0.03277691      b.1     Yes
    #> 2   1.879296  0.3687652 9.57724567      b.2      No