matching_l1: Match observations
In CausalGPS: Matching on Generalized Propensity Scores with Continuous Exposures

Matching function using L1 distance on single exposure level w

matching_l1(
  w,
  dataset,
  e_gps_pred,
  e_gps_std_pred,
  w_resid,
  gps_mx,
  w_mx,
  gps_model = "parametric",
  delta_n = 1,
  scale = 0.5,
  nthread = 1,
  optimized_compile
)

`w`	the targeted single exposure levels.
`dataset`	a completed observational data frame or matrix containing (Y, w, gps, counter, row_index, c).
`e_gps_pred`	a vector of predicted gps values obtained by Machine learning methods.
`e_gps_std_pred`	a vector of predicted std of gps obtained by Machine learning methods.
`w_resid`	the standardized residuals for w.
`gps_mx`	a vector with length 2, includes min(gps), max(gps)
`w_mx`	a vector with length 2, includes min(w), max(w).
`gps_model`	Model type which is used for estimating GPS value, including parametric (default) and non-parametric.
`delta_n`	a specified caliper parameter on the exposure (Default is 1).
`scale`	a specified scale parameter to control the relative weight that is attributed to the distance measures of the exposure versus the GPS estimates (Default is 0.5).
`nthread`	Number of available cores.
`optimized_compile`	An option to activate optimized compilation.