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# First simulated data for the simple linear regression model

`SLM1.Rd`

First 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("SLM1")

## Format

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

`y1`

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

`cte`

  Intercept.

`V`

  Simulated from a normal distribution with a mean of 10 and a variance of 100.

## 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(SLM1, n=5)
    #>           y1 cte         V
    #> 1  82.392059   1 19.001420
    #> 2  -1.942157   1 -1.733458
    #> 3   7.474090   1  1.025146
    #> 4 -12.303381   1 -4.445014
    #> 5  30.378203   1  6.689864
      y = SLM1[,1]
      x = SLM1[,2:3]
      multicollinearity(y, x)
    #>          RVIFs        c0           c3 Scenario Affects
    #> 1 0.0403049717 0.6454323 1.045802e-05      a.1      No
    #> 2 0.0002675731 0.8383436 8.540101e-08      a.1      No