Linear regression

Gene

Transformation (genetics)

Context (archaeology)

Algorithm

Engineering

Biology

Discrete mathematics

Statistics

Covariance matrix

Materials science

Applied mathematics

Archaeology

Distribution (mathematics)

Range (aeronautics)

Cross-sectional regression

Biochemistry

Computer science

Regression analysis

Paleontology

Covariance

Mechanical engineering

Matrix (chemical analysis)

Regression

Mathematics

Geography

Econometrics

Mathematical analysis

Scroll

Composite material

Combinatorics

Regression diagnostic

Chemistry

Polynomial regression

Journal of Econometrics

This paper proposes a context-minimal range of alternative regression models that is used to generate a range of alternative estimates. A prior distribution is assumed with a zero mean but an ambiguous covariance matrix. The choice of the prior covariance matrix is facilitated by transformation to standardized variables which makes the prior expected R2 equal to the sum of the prior variances. Three different ranges of the prior expected R2 are used to define three different intervals of prior covariance matrices which are used to produce three different sets of s-values.

<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.gif" display="inline" overflow="scroll"><mml:mi>S</mml:mi></mml:math>-values: Conventional context-minimal measures of the sturdiness of regression coefficients

S-values: Conventional context-minimal measures of the sturdiness of regression coefficients