A formula approximating degrees of freedom for tree-structured varying coefficient models is proposed to improve BIC model selection over naive parameter counting.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Demographic-only LLM agents for retirement survey prediction exhibit central tendency bias, fail to reproduce incorrect or 'don't know' answers, and miss factor interactions in regressions, unlike survey-anchored agents.
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A tool to determine the degrees of freedom in tree-structured varying coefficient models
A formula approximating degrees of freedom for tree-structured varying coefficient models is proposed to improve BIC model selection over naive parameter counting.
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From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes
Demographic-only LLM agents for retirement survey prediction exhibit central tendency bias, fail to reproduce incorrect or 'don't know' answers, and miss factor interactions in regressions, unlike survey-anchored agents.