$6\mathrm{.}6$ LAB: Backward selection using ols$()$

The forestfires.csv data base contains meteorological information and the area burned for $517$ forest fires that occurred in Montesinho Natural Park in Portugal. The columns of interest are FFMC$,$ DMC$,$ DC$,$ and ISI, as well as the response variable, area.

Read in the file forestfires.csv$.$

Use the ols$()$ function to perform forward selection stepwise regression on the variables FFMC$,$ DMC$,$ DC$,$ and ISI, in that order.

Continue the stepwise regression until all the variables in the model have p$-$values less than $0\mathrm{.}15.$

Ex: If the variable RH is used instead of FFMC$,$ the output is:

model$1$ p$-$values are Intercept $1\mathrm{.}684306$e$-64$

RH $3\mathrm{.}486263$e$-01$

DMC $2\mathrm{.}350870$e$-02$

DC $1\mathrm{.}556796$e$-03$

ISI $6\mathrm{.}984705$e$-01$

dtype: float$64$

model$2$ p$-$value is Intercept $3\mathrm{.}247158$e$-76$

RH $3\mathrm{.}108264$e$-01$

DMC $2\mathrm{.}520680$e$-02$

DC $1\mathrm{.}521100$e$-03$

dtype: float$64$

model$3$ p$-$value is Intercept $2\mathrm{.}969390$e$-136$

DMC $1\mathrm{.}642624$e$-02$

DC $9\mathrm{.}065366$e$-04$

dtype: float$64$