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Highly Cited

2014

Highly Cited

2014

Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be…

Highly Cited

2004

Highly Cited

2004

FITTING DATA WITH NONLINEAR REGRESSION FITTING DATA WITH LINEAR REGRESSION MODELS HOW NONLINEAR REGRESSION WORKS CONFIDENCE…

Highly Cited

2001

Highly Cited

2001

We describe a Bayesian method, for fitting curves to data drawn from an exponential family, that uses splines for which the…

Highly Cited

1998

Highly Cited

1998

A method of estimating a variety of curves by a sequence of piecewise polynomials is proposed, motivated by a Bayesian model and…

Highly Cited

1996

Highly Cited

1996

Part 1 Spline functions: univariate splines bivariate splines. Part 2 Curve fitting: an introduction least-squares spline curve…

Highly Cited

1996

Highly Cited

1996

SUMMARY Problems of regression smoothing and curve fitting are addressed via predictive inference in a flexible class of mixture…

Highly Cited

1986

Highly Cited

1986

The purpose of this book is to reveal to the interested (but perhaps mathematically unsophisticated) user the foundations and…

Highly Cited

1981

Highly Cited

1981

A new paradigm, Random Sample Consensus (RANSAC), for fitting a model to experimental data is introduced. RANSAC is capable of…

Highly Cited

1978

Highly Cited

1978

The optimal design problem is tackled in the framework of a new model and new objectives. A regression model is proposed in which…

Highly Cited

1970

Highly Cited

1970

A new mathematical method is developed for interpolation from a given set of data points in a plane and for fitting a smooth…