docstr: Get estimate of sampling of Y|X=x for each x in x_test.
  
  Parameters
  ----------
  x_test
  
  Returns
  -------
  list
      list of lists
docstr_tok: ["Get","estimate","of","sampling","of","Y|X=x","for","each","x","in","x_test",".","Parameters","--","--","--","--","--","x_test","Returns","--","--","--","-","list","list","of","lists"]
code: def estimate_dist(self, x_test: List[List[float]]) -> List:
      """
      Get estimate of sampling of Y|X=x for each x in x_test.
  
      Parameters
      ----------
      x_test
  
      Returns
      -------
      list
          list of lists
      """
      predicted_samples = []
      for pt in x_test:
          pred = self.model.predict(np.array([pt]))[0]
          closest_pred = self.get_closest_pt(
              self.sorted_train_preds, pred
          )
          predicted_samples.append(
              self.id_to_bins[self.preds_to_id[closest_pred]]
          )
      return predicted_samples
  
imports: from typing import Any, Dict, List, Optional, Union
  import copy
  import numpy
  import pandas
  import xgboost
  import gc
  from collections import defaultdict
  from gluonts.core.component import equals, validated
label_desc: Use image node_id 10 for calling the QRX obj's underlying member method code with example usage: obj.estimate_dist(x_test) and returns: predicted_samples