| System for modelling censored regression models using finite mixture process in econometric application, has estimator that yields valid estimates in cases with high degree of censoring, where estimator is operated Monte Carlo simulation mode based on semi-parametric regression models | |
| 2023-10-16 | |
| 专利权人 | BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard) |
| 申请日期 | 2023-10-16 |
| 专利号 | IN202341069503-A |
| 成果简介 | NOVELTY - The system suggests finite mixture of models for estimation of regression models with a censored response variable. An estimator yields valid estimates in cases with a high degree of censoring. The estimator is operated a Monte Carlo simulation mode compared with earlier suggestions of estimators based on semi-parametric censored regression models. The mixture is utilized for modeling an unknown distribution and adapting the model for estimation of censored regression models extends the partially adaptive estimator, where the distribution of the disturbance term, with the constant term added, is modeled by a mixture of normal distributions. USE - System for modelling censored regression models using finite mixture process in an econometric application and regression analysis. ADVANTAGE - The system avoids the problem of an unbounded log-likelihood function, which is made possible by variances not bounded away from zero, by restricting the parameter space for the variances. |
| IPC 分类号 | G06F-017/18 ; G06N-020/00 ; G06N-005/00 ; G06Q-050/00 ; G09B-019/00 |
| 国家 | 印度 |
| 专业领域 | 信息技术 |
| 语种 | 英语 |
| 成果类型 | 专利 |
| 文献类型 | 科技成果 |
| 条目标识符 | http://119.78.100.226:8889/handle/3KE4DYBR/19626 |
| 专题 | 中国科学院新疆生态与地理研究所 |
| 作者单位 | BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard) |
| 推荐引用方式 GB/T 7714 | RAMACHANDRAN V,CHIDAMBARAM K,NAVEENCHANDRAN P,et al. System for modelling censored regression models using finite mixture process in econometric application, has estimator that yields valid estimates in cases with high degree of censoring, where estimator is operated Monte Carlo simulation mode based on semi-parametric regression models. IN202341069503-A[P]. 2023. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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