Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the effort estimation studies,  can obtain open datasets from the past research. Those datasets are either within-company or cross-company dataset. On effort estimation, it was long discussed which dataset is appropriate for building accurate model. To find a new viewpoint in this discussion,  introduce the causal-effect relationship estimation technique.  use a simple Bayesian approach that is defined by the data generation model in a Linear Non-Gaussian Acyclic Model (LiNGAM). This model is applied to the function point and effort metrics in both within-company and cross-company datasets.  assume that if a dataset is appropriate for effort estimation, causal-effect relationships beten metrics and effort will be extracted more. The result of case study shows that  can extract more causal-effect relationships from the cross-company dataset than that of from the within-company dataset.
['Masanari Kondo', 'Osamu Mizuno']
I am writing a research paper on a idea Analysis on Causal-Effect Relationship in Effort Metrics Using Bayesian LiNGAM
[{"from": "human", "value": "I am writing a research paper on a idea Analysis on Causal-Effect Relationship in Effort Metrics Using Bayesian LiNGAM"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the effort estimation studies,  can obtain open datasets from the past research. Those datasets are either within-company or cross-company dataset. On effort estimation, it was long discussed which dataset is appropriate for building accurate model. To find a new viewpoint in this discussion,  introduce the causal-effect relationship estimation technique.  use a simple Bayesian approach that is defined by the data generation model in a Linear Non-Gaussian Acyclic Model (LiNGAM). This model is applied to the function point and effort metrics in both within-company and cross-company datasets.  assume that if a dataset is appropriate for effort estimation, causal-effect relationships beten metrics and effort will be extracted more. The result of case study shows that  can extract more causal-effect relationships from the cross-company dataset than that of from the within-company dataset."}]