docstr: Checks that unconstrained parameters yield finite joint densities.
code: def testSP500(self):
      """Checks that unconstrained parameters yield finite joint densities."""
      model = stochastic_volatility.StochasticVolatilitySP500(
          use_markov_chain=True
      )
      self.validate_log_prob_and_transforms(
          model,
          sample_transformation_shapes=dict(
              identity={
                  "persistence_of_volatility": [],
                  "mean_log_volatility": [],
                  "white_noise_shock_scale": [],
                  "log_volatility": [2516],
              }
          ),
          check_ground_truth_mean_standard_error=True,
          check_ground_truth_mean=True,
          check_ground_truth_standard_deviation=True,
      )
  
file_path: probability/spinoffs/inference_gym/inference_gym/targets/stochastic_volatility_test.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from inference_gym.internal import data
  from inference_gym.internal import test_util
  from inference_gym.targets import stochastic_volatility
label_desc: Use image node_id 4 for calling the StochasticVolatilityTest obj's underlying member method code with example usage: obj.testSP500() without return types