class_docstr: The abstract class provides the basic structure for all model components
  
  Methods:
      createEvaluation: create the initial evaluation matrix
      createTransition: create the initial transition matrix
      createCovPrior: create a simple prior covariance matrix
      createMeanPrior: create a simple prior latent state
      checkDimensions: if user supplies their own covPrior and meanPrior, this can 
                       be used to check if the dimension matches
class_docstr_tok: ["The","abstract","class","provides","the","basic","structure","for","all","model","components","Methods",":","createEvaluation",":","create","the","initial","evaluation","matrix","createTransition",":","create","the","initial","transition","matrix","createCovPrior",":","create","a","simple","prior","covariance","matrix","createMeanPrior",":","create","a","simple","prior","latent","state","checkDimensions",":","if","user","supplies","their","own","covPrior","and","meanPrior",",","this","can","be","used","to","check","if","the","dimension","matches"]
docstr: All members that need to be initialized.
docstr_tok: ["All","members","that","need","to","be","initialized","."]
code: def __init__(self):
      """All members that need to be initialized."""
      self.d = None
      self.name = None
      self.componentType = None
      self.discount = None
      self.evaluation = None
      self.transition = None
      self.covPrior = None
      self.meanPrior = None
  
file_path: pydlm/pydlm/modeler/component.py
imports: from abc import ABCMeta, abstractmethod
label_desc: Use image node_id 1 to create a new component object  with example: obj = component()