After the pseudo population dataset was generated, we apply outcome models on the pseudo population as-if the dataset is from a randomized experiment.

We propose three types of outcome models using parametric, semi-parametric and non-parametric approaches, respectively.

** estimate_pmetric_erf** estimates the
hazard ratios using a parametric regression model. By default, call

**library to implement generalized nonlinear models.**

`gnm`

** estimate_semipmetric_erf** estimates the
smoothed exposure-response function using a generalized additive model
with splines. By default, call

**library to implement generalized additive models.**

`gam`

** estimate_npmetric_erf** estimates the
smoothed exposure-response function using a kernel smoothing approach.
By default, call

**library to implement local polynomial fitting with a kernel weight. We use a data-driven bandwidth selection.**

`KernSmooth`