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A note on minimax robustness of designs against correlated or heteroscedastic responses

Biometrika, 2024-09, Vol.111 (3), p.1071-1075

Wiens, D P

2024

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Robust discrimination designs

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2009-09, Vol.71 (4), p.805-829

Wiens, Douglas P.

2009

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Comparison of nonlinear height–diameter functions for major Alberta tree species

Canadian journal of forest research, 1992-09, Vol.22 (9), p.1297-1304

1992

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Robust weights and designs for biased regression models: Least squares and generalized M-estimation

Journal of statistical planning and inference, 2000-02, Vol.83 (2), p.395-412

Wiens, Douglas P.

2000

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Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

Forest ecology and management, 2009-09, Vol.258 (7), p.1235-1247

2009

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Minimax designs for approximately linear regression

Journal of statistical planning and inference, 1992-06, Vol.31 (3), p.353-371

Wiens, Douglas P.

1992

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Jackknifing, weighting, diagnostics and variance estimation in generalized M-estimation

Statistics & probability letters, 2000-02, Vol.46 (3), p.287-299

2000

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Integer-Valued, Minimax Robust Designs for Estimation and Extrapolation in Heteroscedastic, Approximately Linear Models

Journal of the American Statistical Association, 2000-09, Vol.95 (451), p.807-818

2000

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Minimax regression designs for approximately linear models with autocorrelated errors

Journal of statistical planning and inference, 1996-10, Vol.55 (1), p.95-106

1996

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Minimax Robust Designs and Weights for Approximately Specified Regression Models with Heteroscedastic Errors

Journal of the American Statistical Association, 1998-12, Vol.93 (444), p.1440-1450

Wiens, Douglas P.

1998

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Sampling with partial replacement extended to include growth projections

Forest science, 1996-08, Vol.42 (3), p.328-334

1996

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A note on the computation of robust, bounded influence estimates and test statistics in regression

Computational statistics & data analysis, 1992-03, Vol.13 (2), p.211-220

Wiens, Douglas P.

1992

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Robustness in spatial studies II: minimax design

Environmetrics (London, Ont.), 2005-03, Vol.16 (2), p.205-217

Wiens, Douglas P.

2005

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Robustness in spatial studies I: minimax prediction

Environmetrics (London, Ont.), 2005-03, Vol.16 (2), p.191-203

Wiens, Douglas P.

2005

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Robust Designs Based on the Infinitesimal Approach

Journal of the American Statistical Association, 1997-12, Vol.92 (440), p.1503-1511

1997

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The detection of coastal-trapped waves

Journal of Geophysical Research, Washington, DC, 1991-02, Vol.96 (C2), p.2593-2597

1991

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Robust regression designs for approximate polynomial models

Journal of statistical planning and inference, 2003-12, Vol.117 (2), p.305-321

2003

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Robust allocation schemes for clinical trials with prognostic factors

Journal of statistical planning and inference, 2005, Vol.127 (1), p.323-340

Wiens, Douglas P.

2005

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On some pattern-reduction matrices which appear in statistics

Linear algebra and its applications, 1985-01, Vol.67, p.233-258

Wiens, Douglas P.

1985

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02.3.2. Badly Weighted Least Squares—Solution

Econometric theory, 2003-08, Vol.19 (4), p.701-703

Wiens, Douglas P.

2003

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Minimax Variance M-Estimators in ε-Contamination Models

The Annals of statistics, 1985-09, Vol.13 (3), p.1078-1096

1985

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Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy

Biometrics, 2001, Vol.57 (4), p.1275-1276

Wiens, D. P.

2001

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Robust sequential designs for nonlinear regression

Canadian journal of statistics, 2002-12, Vol.30 (4), p.601-618

2002

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Asymptotic minimax properties of M-estimators of scale

Statistics & probability letters, 1990-10, Vol.10 (5), p.363-368

1990

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On the exact distribution of the sum of the largest n−k out of n normal random variables with differing mean values

Statistics (Berlin, DDR), 2006-04, Vol.40 (2), p.165-173

2006

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A note on minimax robustness of designs against correlated or heteroscedastic responses

Robust discrimination designs

Comparison of nonlinear height–diameter functions for major Alberta tree species

Robust weights and designs for biased regression models: Least squares and generalized M-estimation

Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

Minimax designs for approximately linear regression

Jackknifing, weighting, diagnostics and variance estimation in generalized M-estimation

Integer-Valued, Minimax Robust Designs for Estimation and Extrapolation in Heteroscedastic, Approximately Linear Models

Minimax regression designs for approximately linear models with autocorrelated errors

Minimax Robust Designs and Weights for Approximately Specified Regression Models with Heteroscedastic Errors

Sampling with partial replacement extended to include growth projections

A note on the computation of robust, bounded influence estimates and test statistics in regression

Robustness in spatial studies II: minimax design

Robustness in spatial studies I: minimax prediction

Robust Designs Based on the Infinitesimal Approach

The detection of coastal-trapped waves

Robust regression designs for approximate polynomial models

Robust allocation schemes for clinical trials with prognostic factors

On some pattern-reduction matrices which appear in statistics

02.3.2. Badly Weighted Least Squares—Solution

Minimax Variance M-Estimators in ε-Contamination Models

Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy

Robust sequential designs for nonlinear regression

Asymptotic minimax properties of M-estimators of scale

On the exact distribution of the sum of the largest n−k out of n normal random variables with differing mean values

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