Measurement Error in Nonlinear Models

Carroll, R. J., Ruppert, Stefanski, & Crainiceanu, C. M. (2006). Measurement Error in Nonlinear Models: A Modern Perspective. Chapman & Hall.

Type

Book

Intellectual base

Review or monograph

Year

2006

Link

https://openlibrary.org/isbn/9781420010138verified

Cited from

statistics_experimental_design

Cited by

1 citation across 1 artifact.

Primes

• Measurement Uncertainty and Observational Noise
  • This prime makes visible the distinction between "the true value exists but we don't know it precisely" (epistemic uncertainty that improves with more observation) and "the measurement apparatus has built-in precision limits" (noise that cannot be eliminated, only managed), a structural-versus-classical-error distinction Carroll, Ruppert, Stefanski, and Crainiceanu (2006) formalize in their measurement-error-models framework.

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