PROTECTED SOURCE SCRIPT
Statistical Mapping [Version 3]

Edit Statistical Mapping (ESM) is a statistical technique used mainly in data validation, error detection, and imputation. It’s often applied in official statistics and large surveys. The method works by:
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
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受保护脚本
此脚本以闭源形式发布。 但是,您可以自由使用,没有任何限制 — 了解更多信息这里。
免责声明
这些信息和出版物并非旨在提供,也不构成TradingView提供或认可的任何形式的财务、投资、交易或其他类型的建议或推荐。请阅读使用条款了解更多信息。