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Computational Methods for Measuring the Difference of Empirical Distributions

Poe, Gregory L.; Giraud, Kelly L.; Loomis, John B. - In: American Journal of Agricultural Economics 87 (2005) 2, pp. 353-365

This paper presents a simple computational method for measuring the difference of independent empirical distributions estimated by bootstrapping or other resampling approaches. Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared...

Persistent link: https://www.econbiz.de/10009392860

Simple Computational Methods for Measuring the Difference of Empirical Distributions: Application to Internal and External Scope Tests in Contingent Valuation

Poe, Gregory L.; Giraud, Kelly L.; Loomis, John B. - Charles H. Dyson School of Applied Economics and … - 2001

Persistent link: https://www.econbiz.de/10009653847

Computational Methods for Measuring the Difference of Empirical Distributions

Giraud, Kelly L.; Loomis, John B. - In: American Journal of Agricultural Economics 87 (2005) 2, pp. 353-365

Persistent link: https://www.econbiz.de/10005291040

Modeling hunting demand in the presence of a bag limit, with tests of alternative specifications

Creel, Michael D.; Loomis, John B. - In: Journal of Environmental Economics and Management 22 (1992) 2, pp. 99-113

Persistent link: https://www.econbiz.de/10005298771

Simple Computational Methods for Measuring the Difference of Empirical Distributions: Application to Internal and External Scope Tests in Contingent Valuation

Poe, Gregory L.; Giraud, Kelly L.; Loomis, John B. - Agricultural and Applied Economics Association - AAEA - 2002

This paper develops a statistically unbiased and simple method for measuring the difference of independent empirical distributions estimated by bootstrapping or other simulation approaches. This complete combinatorial method is compared with other unbiased and biased methods that have been...

Persistent link: https://www.econbiz.de/10005320296