# Mechanisms for Locally Private data release for continuous data

Most of the Local Differential Privacy mechanisms I've seen in the literature operate on discrete data, e.g. Randomized Response or RAPPOR. Can you point me to some LDP mechanisms for continuous data (numeric queries) in the literature (e.g. for vectors in $$\mathbb{R}^d$$)? I assume central DP mechanisms, e.g. Laplace or Gaussian, are transferrable, at the expense of excessive noise.