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Computational Methods for Measuring the Difference of Empirical Distributions
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 with...
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| Published in: | American journal of agricultural economics 2005-05, Vol.87 (2), p.353-365 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c651X-27f8c66c8d34f1729b4c4061a17e2ebf0bd4eae36608d88876cf570aa6173bf83 |
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| cites | cdi_FETCH-LOGICAL-c651X-27f8c66c8d34f1729b4c4061a17e2ebf0bd4eae36608d88876cf570aa6173bf83 |
| container_end_page | 365 |
| container_issue | 2 |
| container_start_page | 353 |
| container_title | American journal of agricultural economics |
| container_volume | 87 |
| creator | Poe, Gregory L. Giraud, Kelly L. Loomis, John B. |
| description | 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 with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate. |
| doi_str_mv | 10.1111/j.1467-8276.2005.00727.x |
| format | article |
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Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate.</description><subject>Agricultural economics</subject><subject>Agricultural management</subject><subject>Applied economics</subject><subject>Bootstrap mechanism</subject><subject>Bootstrap method</subject><subject>bootstrapping</subject><subject>C150</subject><subject>Combinatorial analysis</subject><subject>Computation</subject><subject>Computer programs</subject><subject>Confidence interval</subject><subject>Confidence intervals</subject><subject>contingent valuation</subject><subject>Data analysis</subject><subject>Economic models</subject><subject>Economic theory</subject><subject>Economics</subject><subject>Empirical analysis</subject><subject>Empirical research</subject><subject>Endangered species</subject><subject>Estimation methods</subject><subject>Land economics</subject><subject>measuring differences of distributions</subject><subject>Methodology</subject><subject>Nonparametric models</subject><subject>Polynomials</subject><subject>Programming</subject><subject>Q510</subject><subject>Q570</subject><subject>Samples</subject><subject>Sampling</subject><subject>Scientific method</subject><subject>scope testing</subject><subject>Significance level</subject><subject>Social science research</subject><subject>Statistical analysis</subject><subject>Statistical models</subject><subject>Studies</subject><subject>Valuation</subject><issn>0002-9092</issn><issn>1467-8276</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><recordid>eNqNkc9v0zAcxS3EJMrGf8Ah4oC4JPhHYjvH0ha2qRUHhqi4WI5rM4e0DnYiuv9-9oJ6QGPCFzv6vPccfx8AGYIFiut9W6CSspxjRgsMYVVAyDArjs_A7ASegxmEEOc1rPEL8DKENn5CVPMZ2Czcvh8HOVh3kF220cOt24XMOB_PMozeHn5kw63OltYY7fVB6cyZbLXvrbcqOpY2DN42YwoIF-DMyC7oV3_2c_D14-pmcZmvP3-6WszXuaIV2uaYGa4oVXxHSoMYrptSlZAiiZjGujGw2ZVaakIp5DvOOaPKVAxKSREjjeHkHLydcnvvfo06DGJvg9JdJw_ajUEQHlNRWUfhuyeFiDJUcogRidI3f0lbN_o4lCAwIVHIGYwiPomUdyF4bUTv7V76O4GgSH2IVqSxizR2kfoQD32IY7RuJutv2-m7__aJ-fV8dZ1YQok8gG3MI1OeG_t_pOWP_cXrydWGwfmTj9Ca8Sq9L59wbFUfT1j6n4Iywipxuf0uvnxj6-VNvOoDuQdXhLtO</recordid><startdate>200505</startdate><enddate>200505</enddate><creator>Poe, Gregory L.</creator><creator>Giraud, Kelly L.</creator><creator>Loomis, John B.</creator><general>Oxford University Press</general><general>American Agricultural Economics Association</general><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>8BJ</scope><scope>C1K</scope><scope>FQK</scope><scope>JBE</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>200505</creationdate><title>Computational Methods for Measuring the Difference of Empirical Distributions</title><author>Poe, Gregory L. ; 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| fulltext | fulltext |
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| ispartof | American journal of agricultural economics, 2005-05, Vol.87 (2), p.353-365 |
| issn | 0002-9092 1467-8276 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_38172149 |
| source | EconLit s plnými texty; International Bibliography of the Social Sciences (IBSS); JSTOR Archival Journals and Primary Sources Collection; Wiley-Blackwell Read & Publish Collection; BSC - Ebsco (Business Source Ultimate) |
| subjects | Agricultural economics Agricultural management Applied economics Bootstrap mechanism Bootstrap method bootstrapping C150 Combinatorial analysis Computation Computer programs Confidence interval Confidence intervals contingent valuation Data analysis Economic models Economic theory Economics Empirical analysis Empirical research Endangered species Estimation methods Land economics measuring differences of distributions Methodology Nonparametric models Polynomials Programming Q510 Q570 Samples Sampling Scientific method scope testing Significance level Social science research Statistical analysis Statistical models Studies Valuation |
| title | Computational Methods for Measuring the Difference of Empirical Distributions |
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