@partial(jax.jit, static_argnames=("self",))
    def log_likelihood(
        self,
        params,
        central_values,
        inv_covmat,
        fast_kernel_arrays,
        *penalty_funcs_and_args
    ):
        predictions, pdf = self.pred_and_pdf(params, fast_kernel_arrays)
        chi2_val = self.chi2(central_values, predictions, inv_covmat)
        
        penalty_sum = 0.0
        for penalty_func, penalty_args in penalty_funcs_and_args:
            penalty_sum += jnp.sum(penalty_func(*penalty_args), axis=-1)
        
        return -0.5 * (chi2_val + penalty_sum)