Parsimonious Model
This article covers meaning, importance & example of Parsimonious Model from statistical perspective.
What is Parsimonious Model?
Parsimonious model means the simplest model or theory which has the least assumptions and variables but with greatest explanatory power. This principle is used as a logical tool to filter out and unnecessary and aspects from scientific and philosophical arguments that complicate the system pointlessly. Parsimonious technique is to given logical solutions to problems keeping variables limited and not over-complicating a problem.
Importance of Parsimonious Model
One of the principles of reasoning used in science as well as philosophy is the principle of parsimony or Occam’s razor. The name comes from William of Ockham, a 14th century logician and Franciscan monk who used this principle in his philosophical reasoning. His principle proposed that entities should not be multiplied unnecessary i.e. unnecessary assumptions should be avoided for a theory/conclusion.
Often misunderstood, the main feature of this principle is necessity contrary to simplicity as wrongly believed. Instead simplicity is a consequence, i.e. a parsimonious model would be simpler that competing non-parsimonious theories. Hence at no point necessity is to be compromised, so if certain complexities and assumptions are necessary for explanation then they should be included. Hence a truly parsimonious theory/model will not sacrifice comprehensiveness at expense of simplicity and the goal is to create simple models that have the highest explanatory power.
Example of Parsimonious Model
In evolutionary biology to explain tree building, the hypothesis with least evolutionary changes but does explain the available data completely is better as it is parsimonious and does not hypothesize unnecessary and complicated evolutionary changes.
Hence, this concludes the definition of Parsimonious Model along with its overview.
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