Model as MLR model

model_mlr(df, formula)

Arguments

df	The dataframe containing the time series data
formula	Formula to be used for model creation

Examples

model_mlr(mtcars, mpg~.)
#> 
#> Call:
#> stats::arima(x = df[[dvar]], order = c(phi$p, 0, 0), xreg = as.matrix(evar))
#> 
#> Coefficients:
#>       intercept      cyl    disp       hp    drat       wt    qsec      vs
#>         12.3034  -0.1114  0.0133  -0.0215  0.7871  -3.7153  0.8210  0.3178
#> s.e.    15.1633   0.8466  0.0145   0.0176  1.3248   1.5347  0.5921  1.7049
#>           am    gear     carb
#>       2.5202  0.6554  -0.1994
#> s.e.  1.6661  1.2097   0.6714
#> 
#> sigma^2 estimated as 4.609:  log likelihood = -69.85,  aic = 163.71
model_mlr(mtcars, mpg~cyl + hp)
#> 
#> Call:
#> stats::arima(x = df[[dvar]], order = c(phi$p, 0, 0), xreg = as.matrix(evar))
#> 
#> Coefficients:
#>       intercept      cyl       hp
#>         36.9083  -2.2647  -0.0191
#> s.e.     2.0856   0.5482   0.0143
#> 
#> sigma^2 estimated as 9.124:  log likelihood = -80.78,  aic = 169.56