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2011 | OriginalPaper | Buchkapitel

5. Design of Experiments

verfasst von : Prof. Roberto Baragona, Prof. Francesco Battaglia, Prof. Irene Poli

Erschienen in: Evolutionary Statistical Procedures

Verlag: Springer Berlin Heidelberg

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Abstract

In several research areas, such as biology, chemistry, or material science, experimentation is complex, very expensive and time consuming, so an efficient plan of experimentation is essential to achieve good results and avoid unnecessary waste of resources. An accurate statistical design of the experiments is important also to tackle the uncertainty in the experimental results derived from systematic and random errors that frequently obscure the effects under investigation. In this chapter we will first present the essentials of designing experiments and then describe the evolutionary approach to design in high dimensional settings.

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Literatur
Zurück zum Zitat Apolloni B, Bassis S, Marinaro M (2009) New directions in neural networks. IOS Press, The Netherlands Apolloni B, Bassis S, Marinaro M (2009) New directions in neural networks. IOS Press, The Netherlands
Zurück zum Zitat Atkinson A, Donev A, Tobias R (2007) Optimum experimental designs, with SAS. Oxford University Press, Oxford Atkinson A, Donev A, Tobias R (2007) Optimum experimental designs, with SAS. Oxford University Press, Oxford
Zurück zum Zitat Bailey R (2008) Design of comparative experiments. Cambridge University Press, CambridgeCrossRef Bailey R (2008) Design of comparative experiments. Cambridge University Press, CambridgeCrossRef
Zurück zum Zitat Baldi Antognini A, Giovagnoli A, Romano D, Zagoraiou M (2009) Computer simulations for the optimization of technological processes. In: Erto P (ed) Statistics for innovation. Springer, Milan, pp 65–88CrossRef Baldi Antognini A, Giovagnoli A, Romano D, Zagoraiou M (2009) Computer simulations for the optimization of technological processes. In: Erto P (ed) Statistics for innovation. Springer, Milan, pp 65–88CrossRef
Zurück zum Zitat Blum C, Roli A (2003) Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput Surv 35(3):268–308CrossRef Blum C, Roli A (2003) Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput Surv 35(3):268–308CrossRef
Zurück zum Zitat Borgelt C, Kruse R (2002) Graphical models: methods for data analysis and mining. Wiley, New York, NY Borgelt C, Kruse R (2002) Graphical models: methods for data analysis and mining. Wiley, New York, NY
Zurück zum Zitat Cawse J (2003) Experimental design for combinatorial and high throughput material developments. Springer, New York, NY Cawse J (2003) Experimental design for combinatorial and high throughput material developments. Springer, New York, NY
Zurück zum Zitat Cornell J (2002) Experiments with mixtures: designs, models, and the analysis of mixture data. Wiley, New York, NY Cornell J (2002) Experiments with mixtures: designs, models, and the analysis of mixture data. Wiley, New York, NY
Zurück zum Zitat Cowell R, Dawid A, Lauritzen S, Spiegelhalter D (1999) Probabilistic networks and expert systems. Springer, New York, NY Cowell R, Dawid A, Lauritzen S, Spiegelhalter D (1999) Probabilistic networks and expert systems. Springer, New York, NY
Zurück zum Zitat Cox D (1953) Planning of experiments. Wiley, New York, NY Cox D (1953) Planning of experiments. Wiley, New York, NY
Zurück zum Zitat Cox D, Reid N (2000) The theory of the design of experiments. Chapman & Hall, London Cox D, Reid N (2000) The theory of the design of experiments. Chapman & Hall, London
Zurück zum Zitat Darwiche A (2009) Modeling and reasoning with Bayesian networks. Cambridge University Press, Cambridge Darwiche A (2009) Modeling and reasoning with Bayesian networks. Cambridge University Press, Cambridge
Zurück zum Zitat De Jong K (2006) Evolutionary computation. The MIT Press, Cambridge De Jong K (2006) Evolutionary computation. The MIT Press, Cambridge
Zurück zum Zitat De March D, Forlin M, Slanzi D, Poli I (2009a) An evolutionary predictive approach to design high dimensional experiments. In: Serra R, Poli I, Villani M (eds) Artificial life and evolutionary computation: proceedings of WIVACE 2008. World Scientific Publishing Company, Singapore, pp 81–88 De March D, Forlin M, Slanzi D, Poli I (2009a) An evolutionary predictive approach to design high dimensional experiments. In: Serra R, Poli I, Villani M (eds) Artificial life and evolutionary computation: proceedings of WIVACE 2008. World Scientific Publishing Company, Singapore, pp 81–88
Zurück zum Zitat De March D, Slanzi D, Poli I (2009b) Evolutionary algorithms for complex experimental designs. In: Ermakov S, Melas V, Pepelyshev A (eds) Simulation, St. Petersburg VVM com., St. Petersburg, Russia, pp 547–552 De March D, Slanzi D, Poli I (2009b) Evolutionary algorithms for complex experimental designs. In: Ermakov S, Melas V, Pepelyshev A (eds) Simulation, St. Petersburg VVM com., St. Petersburg, Russia, pp 547–552
Zurück zum Zitat Dean A, Voss D (1999) Design and analysis of experiments. Springer, New York, NYCrossRef Dean A, Voss D (1999) Design and analysis of experiments. Springer, New York, NYCrossRef
Zurück zum Zitat Fisher R (1935) The design of experiments. Oliver & Boyd, Edinburgh Fisher R (1935) The design of experiments. Oliver & Boyd, Edinburgh
Zurück zum Zitat Forlin M, Poli I, De March D, Packard N, Gazzola G, Serra R (2008) Evolutionary experiments for self-assembling amphiphilic systems. Chemom Intell Lab Syst 90(2):153–160CrossRef Forlin M, Poli I, De March D, Packard N, Gazzola G, Serra R (2008) Evolutionary experiments for self-assembling amphiphilic systems. Chemom Intell Lab Syst 90(2):153–160CrossRef
Zurück zum Zitat Greenshtein E (2006) Best subset selection, persistence in high-dimensional statistical learning and optimization under l 1 constraint. Ann Stat 34(5):2367–2386MATHCrossRefMathSciNet Greenshtein E (2006) Best subset selection, persistence in high-dimensional statistical learning and optimization under l 1 constraint. Ann Stat 34(5):2367–2386MATHCrossRefMathSciNet
Zurück zum Zitat Greenshtein E, Ritov Y (2004) Persistency in high dimensional linear predictor-selection and the virtue of over-parametrization. Bernoulli 10:971–988MATHCrossRefMathSciNet Greenshtein E, Ritov Y (2004) Persistency in high dimensional linear predictor-selection and the virtue of over-parametrization. Bernoulli 10:971–988MATHCrossRefMathSciNet
Zurück zum Zitat Heckerman D, Geiger D, Chickering D (1995) Learning bayesian networks: the combinations of knowledge and statistical data. Mach Learn 20:197–243MATH Heckerman D, Geiger D, Chickering D (1995) Learning bayesian networks: the combinations of knowledge and statistical data. Mach Learn 20:197–243MATH
Zurück zum Zitat Heredia-Langner A, Carlyle W, Montgomery D, Borror C, Runger G (2003) Genetic algorithms for the construction of d-optimal designs. J Qual Technol 35(1):28–46 Heredia-Langner A, Carlyle W, Montgomery D, Borror C, Runger G (2003) Genetic algorithms for the construction of d-optimal designs. J Qual Technol 35(1):28–46
Zurück zum Zitat Jensen F (2001) Bayesian networks and decision graphs. Springer, New York, NY Jensen F (2001) Bayesian networks and decision graphs. Springer, New York, NY
Zurück zum Zitat Lauritzen SL (1996) Graphical models. Oxford University Press, Oxford Lauritzen SL (1996) Graphical models. Oxford University Press, Oxford
Zurück zum Zitat Lazic Z (2004) Design of experiments in chemical engineering. Wiley-VCH, Weinheim, GermanyCrossRef Lazic Z (2004) Design of experiments in chemical engineering. Wiley-VCH, Weinheim, GermanyCrossRef
Zurück zum Zitat Minervini G, Evangelista G, Villanova L, Slanzi D, De Lucrezia D, Poli I, Luisi P, Polticelli F (2009) Massive non natural proteins structure prediction using grid technologies. BMC Bioinformatics 10(6):S22CrossRef Minervini G, Evangelista G, Villanova L, Slanzi D, De Lucrezia D, Poli I, Luisi P, Polticelli F (2009) Massive non natural proteins structure prediction using grid technologies. BMC Bioinformatics 10(6):S22CrossRef
Zurück zum Zitat Montgomery D (2009) Design and analysis of experiments. Wiley, New York, NY Montgomery D (2009) Design and analysis of experiments. Wiley, New York, NY
Zurück zum Zitat Myers R, Montgomery D, Vining G, Borror C, Kowalski S (2004) Response surface methodology: a retrospective and literature survey. J Qual Technol 36(1):53–77 Myers R, Montgomery D, Vining G, Borror C, Kowalski S (2004) Response surface methodology: a retrospective and literature survey. J Qual Technol 36(1):53–77
Zurück zum Zitat Pelikan M (2005) Hierarchical Bayesian optimization algorithm. Springer, New York, NY Pelikan M (2005) Hierarchical Bayesian optimization algorithm. Springer, New York, NY
Zurück zum Zitat Pistone G, Riccomagno E, Wynn H (2000) Algebraic statistics: computational commutative algebra in statistics. Chapman & Hall/CRC, LondonCrossRef Pistone G, Riccomagno E, Wynn H (2000) Algebraic statistics: computational commutative algebra in statistics. Chapman & Hall/CRC, LondonCrossRef
Zurück zum Zitat Poli I, Jones R (1994) A neural net model for prediction. J Am Stat Assoc 89(425):117–121MATHCrossRef Poli I, Jones R (1994) A neural net model for prediction. J Am Stat Assoc 89(425):117–121MATHCrossRef
Zurück zum Zitat Poli I, Roverato A (1998) A genetic algorithm for graphical model selection. J Ital Stat Soc 2:197–208CrossRef Poli I, Roverato A (1998) A genetic algorithm for graphical model selection. J Ital Stat Soc 2:197–208CrossRef
Zurück zum Zitat Schneider J, Kirkpatrick S (2006) Stochastic optimization. Springer, Berlin Heidelberg Schneider J, Kirkpatrick S (2006) Stochastic optimization. Springer, Berlin Heidelberg
Zurück zum Zitat Slanzi D, De March D, Poli I (2009a) Evolutionary probabilistic graphical models in high dimensional data analysis. In: Mola F, Conversano C, Vinzi V, Fisher N (eds) European regional meeting of the international society for business and industrial statistics, Cagliari, Italy, TAPILA editore, pp 124–125 Slanzi D, De March D, Poli I (2009a) Evolutionary probabilistic graphical models in high dimensional data analysis. In: Mola F, Conversano C, Vinzi V, Fisher N (eds) European regional meeting of the international society for business and industrial statistics, Cagliari, Italy, TAPILA editore, pp 124–125
Zurück zum Zitat Wu C, Hamad M (2000) Experiments. Wiley, New York, NY Wu C, Hamad M (2000) Experiments. Wiley, New York, NY
Zurück zum Zitat Slanzi D, De March D, Poli I (2009b) Probabilistic graphical models in high dimensional systems. In: Ermakov S, Melas V, Pepelyshev A (eds) Simulation. St. Petersburg VVM com., pp 557–561, Saint Petersburg, Russia Slanzi D, De March D, Poli I (2009b) Probabilistic graphical models in high dimensional systems. In: Ermakov S, Melas V, Pepelyshev A (eds) Simulation. St. Petersburg VVM com., pp 557–561, Saint Petersburg, Russia
Zurück zum Zitat Bedau M, Buchanan A, Gazzola G, Hanczyc M, McCaskill J, Poli I, Packard N (2005) Evolutionary design of a ddpd model of ligation. In: Proceedings of the 7th international conference on artificial evolution EA’05 (Lecture notes in computer science), Lille, France, vol 3871, pp 201–212 Bedau M, Buchanan A, Gazzola G, Hanczyc M, McCaskill J, Poli I, Packard N (2005) Evolutionary design of a ddpd model of ligation. In: Proceedings of the 7th international conference on artificial evolution EA’05 (Lecture notes in computer science), Lille, France, vol 3871, pp 201–212
Zurück zum Zitat Borrotti M, De Lucrezia D, Minervini G (2009) Evolutionary experimental design for synthetic protein. Working paper 24, European centre for living technology, Venice, Italy, 2nd workshop of the ERCIM working group on computing & statistics, Limassol, Cyprus Borrotti M, De Lucrezia D, Minervini G (2009) Evolutionary experimental design for synthetic protein. Working paper 24, European centre for living technology, Venice, Italy, 2nd workshop of the ERCIM working group on computing & statistics, Limassol, Cyprus
Zurück zum Zitat Fan J, Li R (2006) Statistical challenges with high dimensionality: feature selection in knowledge discovery. In: Proceedings of the international congress of mathematicians, Madrid, Spain Fan J, Li R (2006) Statistical challenges with high dimensionality: feature selection in knowledge discovery. In: Proceedings of the international congress of mathematicians, Madrid, Spain
Zurück zum Zitat Forlin M (2009) A model-based evolutionary approach to high dimensional experimentation. In: Mola F, Conversano C, Vinzi V, Fisher N (eds) European regional meeting of the international society for business and industrial statistics - EURISBIS’09, Cagliari, Italy, TAPILA editore, pp 120–121 Forlin M (2009) A model-based evolutionary approach to high dimensional experimentation. In: Mola F, Conversano C, Vinzi V, Fisher N (eds) European regional meeting of the international society for business and industrial statistics - EURISBIS’09, Cagliari, Italy, TAPILA editore, pp 120–121
Zurück zum Zitat Forlin M, De March D, Poli I (2007) The model-based genetic algorithms for designing mixture experiments. Working paper 18, European centre for living technology, Venice Forlin M, De March D, Poli I (2007) The model-based genetic algorithms for designing mixture experiments. Working paper 18, European centre for living technology, Venice
Zurück zum Zitat Pizzi C, Parpinel F, Soligo M (2009) Spline regression for an evolutionary approach to experimental design. Working paper 25, European centre for living technology, Venice, 2nd Workshop of the ERCIM Working Group on Computing & Statistics, Cyprus Pizzi C, Parpinel F, Soligo M (2009) Spline regression for an evolutionary approach to experimental design. Working paper 25, European centre for living technology, Venice, 2nd Workshop of the ERCIM Working Group on Computing & Statistics, Cyprus
Zurück zum Zitat Poli I (2006) Evolutionary design of experiments. Working paper 18, European Centre for Living Technology, Venice, PACE Report Poli I (2006) Evolutionary design of experiments. Working paper 18, European Centre for Living Technology, Venice, PACE Report
Zurück zum Zitat Slanzi D, Poli I (2009) Evolutionary bayesian networks for high-dimensional stochastic optimization. Working paper 26, European centre for living technology, Venice, 2nd Workshop of the ERCIM working group on computing & statistics, Cyprus Slanzi D, Poli I (2009) Evolutionary bayesian networks for high-dimensional stochastic optimization. Working paper 26, European centre for living technology, Venice, 2nd Workshop of the ERCIM working group on computing & statistics, Cyprus
Zurück zum Zitat Slanzi D, Poli I, De March D, Forlin M (2008) Bayesian networks for high dimensional experiments. Working paper 20, European centre for living technology, Venice, workshop on Bayesian analysis of high dimensional data, 14–16 Apr 2008, Warwick, UK Slanzi D, Poli I, De March D, Forlin M (2008) Bayesian networks for high dimensional experiments. Working paper 20, European centre for living technology, Venice, workshop on Bayesian analysis of high dimensional data, 14–16 Apr 2008, Warwick, UK
Zurück zum Zitat Theis M, Gazzola G, Forlin M, Poli I, Hanczyc M, Packard N, Bedau M (2008) Optimal formulation of complex chemical systems with a genetic algorithm. Working paper 19, European centre for living technology, Venice Theis M, Gazzola G, Forlin M, Poli I, Hanczyc M, Packard N, Bedau M (2008) Optimal formulation of complex chemical systems with a genetic algorithm. Working paper 19, European centre for living technology, Venice
Zurück zum Zitat Zemella G, De March D (2009) The optimisation of building envelopes with evolutionary procedure. Working paper 27, European Centre for Living Technology, Venice, 2nd workshop of the ERCIM working group on Computing & Statistics, Limassol, Cyprus Zemella G, De March D (2009) The optimisation of building envelopes with evolutionary procedure. Working paper 27, European Centre for Living Technology, Venice, 2nd workshop of the ERCIM working group on Computing & Statistics, Limassol, Cyprus
Metadaten
Titel
Design of Experiments
verfasst von
Prof. Roberto Baragona
Prof. Francesco Battaglia
Prof. Irene Poli
Copyright-Jahr
2011
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-16218-3_5