add `define_infection_model()`

[smwindecker]

where:

define_infection_model <- function (infection_model_type = c('flat_prior',
                                                                            'gp_infections',
                                                                            'gp_growth_rate',
                                                                            'gp_growth_rate_deriv'),
                                                                 n_chains = 4,
                                                                 max_convergence_tries = 3,
                                                                 warmup = 2000,
                                                                 n_samples = 2000,
                                                                 n_extra_samples = 1000) {}

and fit_waves() wraps it to integrate the output from create_observation_model() and this one, for parallelism.