The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Residuals and Influence in Regression.
Abstract
Conlputat ions E.ratnple 2.3.4Jer Jiyhters no.I 2.3.3Partial residual plots Esantple 2.3.5 Jef fiyhrers no. 2 2.3.4Probability plots E.ratrtpIe 2.3.6 Cloud seeditty no. 4 2.4 Transformations 2.4.1 Fanlilies of fratlsjorr~ratiot~s 2.4.2Selectb~g a trat~s/'orrtlatiott Itr~.ariattceNor~rrality Choice c?/'trtodel i ~t t c i scalirlg the predictors It~f'erettce E.uan~ple 2.4.1 Tree data 110.I 2.4.3Diagnostic ntetttods A tkinson 's method Andrew' nterhod Application to the power family Tukey's test E.rample 2.4.2Tree data no. 2 E.~antple 2.4.3Jet fiyhters no. 3 2.4.4Trarrsfor~r~ing the esplana~ory ~lariahles Esatrtple 2.4.4Tree data no. 3 Esatrtple 2.4.5 Cloud see(fittg no. 5 2.5 Residual analysis in two-way tables 2.5.1 Otitliers 2.5.2Nottaciditirity E.\-antple 2.5.1 A y ricultural e-rperintenl 3 Assessment of influence 3.1 Motivation 3.2 The influence curve E.uatrtple 3.2.1The sanlple auerage3.3 The influence curve in the linear model 3.4 Sample versions of the influence curve 3.4.1 E~rtpiricnl ittfl~iet~i-e curves 3.4.2Sotrtple it~fltrettce curres Esntilple 3.4.1 C l o ~i d seeding tlo.6 E.uittr~ple 3.4.2Partial Ffesrs 3.5 Applications of the sample influence curve 3.5.1 Estert~al scalit~g bI = XTX, c = p'62 Euatrtple 3.5.1 C'omhinafion.sqf r f , vii Esanlple 3.5.2Rat data Alrernatice full rank choices for M, c Lower dintensior~al trortrts E.ratiiple 3.5.3Cloud seeding 110.7
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Cites
An analysis of variance test for normality (complete samples)
SHAPIRO, S. S., & WILK, M. B. (1965) · Biometrika · doi:10.1093/biomet/52.3-4.591 · Cited by 23,480
An Analysis of Variance Test for Normality (Complete Samples)
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The Influence Curve and its Role in Robust Estimation
Hampel, F. R. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10482962 · Cited by 2,706
Quasi-likelihood functions, generalized linear models, and the gauss-newton method
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Quasi-likelihood functions, generalized linear models, and the Gauss—Newton method
WEDDERBURN, R. W. M. (1974) · Biometrika · doi:10.1093/biomet/61.3.439 · Cited by 2,122
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Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Fitting Linear Mixed-Effects Models Using lme4
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835
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Metadata
- Authors
- Chatterjee, S., Cook, R. D., & Weisberg, S.
- Venue
- Journal of the American Statistical Association
- Publisher
- JSTOR
- Published
- 1984-12
- Volume
- 79
- Issue
- 388
- Pages
- 951
- ISSN
- 0162-1459 (ISSN-L)
- OpenAlex
- W4302067479
- Cited by
- 622
- References
- 69
- FWCI
- 5.24
- Type
- journal article
- Language
- en
- Open access
- closed
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