Errors-in-variables Regression

Errors-In-Variables Regression is a regression method that accounts for measurement errors in both dependent and independent variables, distinguishing itself from ordinary regression models by explicitly modeling inaccuracies in predictor variables.

515

Publications

39.5K

Citations

807

Authors

460

Institutions

Publications per year

2017–2026

58

Variants

Errors-in-variables Model

Parents

Authors

807

  1. TS
    Torsten Söderström

    Uppsala University, Sweden

    19 publications · 645 citations

    15

    h-index

  2. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    15 publications · 1.6K citations

    13

    h-index

  3. WA
    Wayne A. Fuller

    Iowa State University, United States

    8 publications · 341 citations

    8

    h-index

  4. CC
    Chi-Lun Cheng

    Institute of Statistical Science, Academia Sinica, Taiwan

    7 publications · 578 citations

    7

    h-index

  5. AK
    Alexander Kukush

    Taras Shevchenko National University of Kyiv, Ukraine

    7 publications · 268 citations

    7

    h-index

1–5 of 807

Venues

  1. Journal of the American Statistical Association

    40 publications · 3.6K citations

    27

    h-index

  2. Automatica

    21 publications · 912 citations

    19

    h-index

  3. Journal of Econometrics

    20 publications · 2.7K citations

    17

    h-index

  4. Econometrica

    13 publications · 1.9K citations

    12

    h-index

  5. Journal of Multivariate Analysis

    12 publications · 531 citations

    12

    h-index

1–5