Optimisation in space of measures and optimal design

Molchanov, Ilya; Zuyev, Sergei

doi:10.1051/ps:2003016

Molchanov, Ilya ; Zuyev, Sergei

ESAIM: Probability and Statistics, Tome 8 (2004), pp. 12-24.

Résumé

The paper develops an approach to optimal design problems based on application of abstract optimisation principles in the space of measures. Various design criteria and constraints, such as bounded density, fixed barycentre, fixed variance, etc. are treated in a unified manner providing a universal variant of the Kiefer-Wolfowitz theorem and giving a full spectrum of optimality criteria for particular cases. Incorporating the optimal design problems into conventional optimisation framework makes it possible to use the whole arsenal of descent algorithms from the general optimisation literature for finding optimal designs. The corresponding steepest descent involves adding a signed measure at every step and converges faster than the conventional sequential algorithms used to construct optimal designs. We study a new class of design problems when the observation points are distributed according to a Poisson point process arising in the situation when the total control on the placement of measurements is impossible.

MR Zbl

DOI : 10.1051/ps:2003016

Classification : 62K05, 49K45, 60G55
Mots-clés : optimal experimental design, generalized equivalence theorem, constrained optimal design, Poisson design, optimization on measures, gradient methods

@article{PS_2004__8__12_0,
     author = {Molchanov, Ilya and Zuyev, Sergei},
     title = {Optimisation in space of measures and optimal design},
     journal = {ESAIM: Probability and Statistics},
     pages = {12--24},
     publisher = {EDP-Sciences},
     volume = {8},
     year = {2004},
     doi = {10.1051/ps:2003016},
     mrnumber = {2085602},
     zbl = {1031.62058},
     language = {en},
     url = {http://archive.numdam.org/articles/10.1051/ps:2003016/}
}

TY  - JOUR
AU  - Molchanov, Ilya
AU  - Zuyev, Sergei
TI  - Optimisation in space of measures and optimal design
JO  - ESAIM: Probability and Statistics
PY  - 2004
SP  - 12
EP  - 24
VL  - 8
PB  - EDP-Sciences
UR  - http://archive.numdam.org/articles/10.1051/ps:2003016/
DO  - 10.1051/ps:2003016
LA  - en
ID  - PS_2004__8__12_0
ER  -

%0 Journal Article
%A Molchanov, Ilya
%A Zuyev, Sergei
%T Optimisation in space of measures and optimal design
%J ESAIM: Probability and Statistics
%D 2004
%P 12-24
%V 8
%I EDP-Sciences
%U http://archive.numdam.org/articles/10.1051/ps:2003016/
%R 10.1051/ps:2003016
%G en
%F PS_2004__8__12_0

Molchanov, Ilya; Zuyev, Sergei. Optimisation in space of measures and optimal design. ESAIM: Probability and Statistics, Tome 8 (2004), pp. 12-24. doi : 10.1051/ps:2003016. http://archive.numdam.org/articles/10.1051/ps:2003016/

Bibliographie
Cité par

[1] A.C. Atkinson and A.N. Donev, Optimum Experimental Designs. Clarendon Press, Oxford (1992). | Zbl

[2] C.L. Atwood, Sequences converging to $D$ -optimal designs of experiments. Ann. Statist. 1 (1973) 342-352. | MR | Zbl

[3] C.L. Atwood, Convergent design sequences, for sufficiently regular optimality criteria. Ann. Statist. 4 (1976) 1124-1138. | MR | Zbl

[4] D. Böhning, A vertex-exchange-method in $D$ -optimal design theory. Metrika 33 (1986) 337-347. | MR | Zbl

[5] R. Cominetti, Metric regularity, tangent sets, and second-order optimality conditions. Appl. Math. Optim. 21 (1990) 265-287. | MR | Zbl

[6] D. Cook and V. Fedorov, Constrained optimization of experimental design. Statistics 26 (1995) 129-178. | MR | Zbl

[7] D.J. Daley and D. Vere-Jones, An Introduction to the Theory of Point Processes. Springer, New York (1988). | Zbl

[8] N. Dunford and J.T. Schwartz, Linear Operators. Part I: General Theory. Wiley, New York (1988). | MR | Zbl

[9] V.V. Fedorov, Theory of Optimal Experiments. Academic Press, New York (1972). | MR | Zbl

[10] V.V. Fedorov, Optimal design with bounded density: Optimization algorithms of the exchange type. J. Statist. Plan. Inf. 22 (1989) 1-13. | MR | Zbl

[11] V.V. Fedorov and P. Hackl, Model-Oriented Design of Experiments. Springer, New York, Lecture Notes in Statist. 125 (1997). | MR | Zbl

[12] I. Ford, Optimal Static and Sequential Design: A Critical Review, Ph.D. Thesis. Department of Statistics, University of Glasgow, Glasgow (1976).

[13] A. Gaivoronski, Linearization methods for optimization of functionals which depend on probability measures. Math. Progr. Study 28 (1986) 157-181. | MR | Zbl

[14] N. Gaffke and R. Mathar, On a Class of Algorithms from Experimental Design Theory. Optimization 24 (1992) 91-126. | MR | Zbl

[15] E. Hille and R.S. Phillips, Functional Analysis and Semigroups. American Mathematical Society, Providence, AMS Colloquium Publications XXXI (1957). | MR | Zbl

[16] J. Kiefer, General equivalence theory for optimum designs (approximate theory). Ann. Statist. 2 (1974) 849-879. | MR | Zbl

[17] J. Kiefer and J. Wolfowitz, The equivalence of two extremal problems. Canad. J. Math. 14 (1960) 363-366. | MR | Zbl

[18] P. Kumaravelu, L. Hook, A.M. Morrison, J. Ure, S. Zhao, S. Zuyev, J. Ansell and A. Medvinsky, Quantitative developmental anatomy of definitive haematopoietic stem cells/long-term repopulating units (HSC/RUs): Role of the aorta-gonad-mesonephros (AGM) region and the yolk sac in colonisation of the mouse embryonic liver. Development 129 (2002) 4891-4899.

[19] E.P. Liski, N.K. Mandal, K.R. Shah and B.K. Singha, Topics in Optimal Design. Springer, New York, Lect. Notes Statist. 163 (2002). | MR | Zbl

[20] H. Maurer and J. Zowe, First and second-order necessary and sufficient optimality conditions for infinite-dimensional programming problems. Math. Programming 16 (1979) 98-110. | MR | Zbl

[21] I. Molchanov and S. Zuyev, Steepest descent algorithms in space of measures. Statist. and Comput. 12 (2002) 115-123. | MR

[22] I. Molchanov and S. Zuyev, Tangent sets in the space of measures: With applications to variational calculus. J. Math. Anal. Appl. 249 (2000) 539-552. | MR | Zbl

[23] I. Molchanov and S. Zuyev, Variational analysis of functionals of a Poisson process. Math. Oper. Res. 25 (2000) 485-508. | MR | Zbl

[24] C.H. Müller and A. Pázman, Applications of necessary and sufficient conditions for maximin efficient designs. Metrika 48 (1998) 1-19. | MR | Zbl

[25] A. Pázman, Hilbert-space methods in experimantal design. Kybernetika 14 (1978) 73-84. | MR | Zbl

[26] E. Polak, Optimization. Algorithms and Consistent Approximations. Springer, New York (1997). | MR | Zbl

[27] F. Pukelsheim, Optimal Design of Experiments. Wiley, New York (1993). | MR | Zbl

[28] S.M. Robinson, First order conditions for general nonlinear optimization. SIAM J. Appl. Math. 30 (1976) 597-607. | MR | Zbl

[29] S.D. Silvey, Optimum Design. Chapman & Hall, London (1980). | MR | Zbl

[30] D. Stoyan, W.S. Kendall and J. Mecke, Stochastic Geometry and its Applications, Second Edition. Wiley, Chichester (1995). | MR | Zbl

[31] P. Whittle, Some general points in the theory of optimal experimental design. J. Roy. Statist. Soc. Ser. B 35 (1973) 123-130. | MR | Zbl

[32] G. Winkler, Extreme points of moment sets. Math. Oper. Res. 13 (1988) 581-587. | MR | Zbl

[33] C.-F. Wu, Some algorithmic aspects of the theory of optimal design. Ann. Statist. 6 (1978) 1286-1301. | MR | Zbl

[34] C.-F. Wu, Some iterative procedures for generating nonsingular optimal designs. Comm. Statist. Theory Methods A 7 (1978) 1399-1412. | Zbl

[35] C.-F. Wu and H.P. Wynn, The convergence of general step-length algorithms for regular optimum design criteria. Ann. Statist. 6 (1978) 1273-1285. | MR | Zbl

[36] H.P. Wynn, The sequential generation of $D$ -optimum experimental designs. Ann. Math. Statist. 41 (1970) 1655-1664. | MR | Zbl

[37] H.P. Wynn, Results in the theory and construction of $D$ -optimum experimental designs. J. Roy. Statist. Soc. Ser. B 34 (1972) 133-147. | MR | Zbl

[38] J. Zowe and S. Kurcyusz, Regularity and stability for the mathematical programming problem in Banach spaces. Appl. Math. Optim. 5 (1979) 49-62. | MR | Zbl

Cité par Sources :