Identifiable up to rearrangement

junpenglao · May 25, 2019, 6:13am

Nope, most likely NUTS will try to do sample all the space and failed, see eg Identifying Bayesian Mixture Models

One solution I can think of is to port the permutation bijector from TFP into a transformer in pymc3.

tensorflow/probability/blob/main/tensorflow_probability/python/bijectors/permute.py

# Copyright 2018 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Permutation bijectors."""

# Dependency imports
import numpy as np

import tensorflow.compat.v2 as tf

This file has been truncated. show original

One solution

Topic		Replies	Views
Divergences and label-switching in a Dirichlet process mixture model Questions	2	1334	July 18, 2021
Label switching in multivariate mixtures Questions	0	765	September 28, 2020
Constraining order in a Mixture model Questions	6	1440	August 9, 2021
Constrain one variable to be greater than another Questions	14	3519	January 30, 2018
Why does `transform=pm.distributions.transforms.ordered` lead to worse convergence? Questions	3	1579	August 27, 2021

Identifiable up to rearrangement

Related topics