Confidence bounds and hypothesis tests for normal distribution coefficients of variation /
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| Language: | English |
|---|---|
| Format: | U.S. Federal Government Document Book E-Resource |
| _version_ | 1819230952517271552 |
|---|---|
| author | Verrill, S. P. |
| author2 | Johnson, Richard A. Forest Products Laboratory (U.S.) |
| author_browse | Verrill, S. P. Johnson, Richard A. Forest Products Laboratory (U.S.) |
| author_facet | Verrill, S. P. Johnson, Richard A. Forest Products Laboratory (U.S.) Verrill, S. P. Johnson, Richard A. Forest Products Laboratory (U.S.) |
| author_sort | Verrill, S. P. |
| building | Internet |
| collection | Hathi Collection |
| contents | Cover title. "September 2007"--P. [2] of cover. For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from [the square root of n]-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramér condition approach and make the conditions and their use explicit. Keywords: coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, [the square root of n]-consistent estimators, efficient likelihood estimators, Cramér conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics. |
| ctrlnum | (OCoLC)181163626 |
| format | U.S. Federal Government Document Book E-Resource |
| fullrecord | 02258cam a2200349Ia 4500001001300000007000300013003000600016005001700022008004100039040002800080035002100108050002400129070002500153086002300178049000900201100001900210245013300229260007700362300002800439440003300467500001700500500003900517530004200556504005200598520104500650650005501695650002601750700002401776710003801800856005801838994001201896 ocn181163626 cr OCoLC 20100309091506.0 071114s2007 wiua b f000 0 eng aAGL cAGL dAGL dORE dMTG a(OCoLC)181163626 14 aSD433 b.U575 no.638 0 aaQA276.74 b.V47 2007 0 aA 13.78:FPL-RP-638 aCGUA 1 aVerrill, S. P. 10 aConfidence bounds and hypothesis tests for normal distribution coefficients of variation / cSteve P. Verril, Richard A. Johnson. aMadison, WI : bUSDA, Forest Service, Forest Products Laboratory, c[2007] a57 p. : bill. ; c28 cm. 0 aResearch paper FPL-RP ; v638 aCover title. a"September 2007"--P. [2] of cover. aAlso available on the World Wide Web. aIncludes bibliographical references (p. 11-12). 3 aFor normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from [the square root of n]-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramér condition approach and make the conditions and their use explicit. Keywords: coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, [the square root of n]-consistent estimators, efficient likelihood estimators, Cramér conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics. 0 aStatistical hypothesis testing xAsymptotic theory. 0 aConfidence intervals. 1 aJohnson, Richard A. 2 aForest Products Laboratory (U.S.) 41 uhttp://www.fpl.fs.fed.us/documnts/fplrp/fpl_rp638.pdf aC0 bCGU |
| id | ocn181163626 |
| illustrated | Illustrated |
| import_time | 2024-12-23T11:37:14.642Z |
| institution | The University of Chicago |
| language | English |
| notes | Cover title. "September 2007"--P. [2] of cover. Also available on the World Wide Web. Includes bibliographical references (p. 11-12). For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from [the square root of n]-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramér condition approach and make the conditions and their use explicit. Keywords: coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, [the square root of n]-consistent estimators, efficient likelihood estimators, Cramér conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics. |
| oclc_num | 181163626 |
| physical | 57 p. : ill. ; 28 cm. |
| publication_place | Madison, WI : |
| publishDate | 2007 |
| publisher | USDA, Forest Service, Forest Products Laboratory, |
| recordtype | hathi |
| series | Research paper FPL-RP |
| series_browse | Research paper FPL-RP |
| series_facet | Research paper FPL-RP |
| spelling | Verrill, S. P. Confidence bounds and hypothesis tests for normal distribution coefficients of variation / Steve P. Verril, Richard A. Johnson. Madison, WI : USDA, Forest Service, Forest Products Laboratory, [2007] 57 p. : ill. ; 28 cm. Research paper FPL-RP ; 638 Cover title. "September 2007"--P. [2] of cover. Also available on the World Wide Web. Includes bibliographical references (p. 11-12). For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from [the square root of n]-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramér condition approach and make the conditions and their use explicit. Keywords: coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, [the square root of n]-consistent estimators, efficient likelihood estimators, Cramér conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics. Statistical hypothesis testing Asymptotic theory. Confidence intervals. Johnson, Richard A. Forest Products Laboratory (U.S.) http://www.fpl.fs.fed.us/documnts/fplrp/fpl_rp638.pdf |
| spellingShingle | Verrill, S. P. Confidence bounds and hypothesis tests for normal distribution coefficients of variation / Research paper FPL-RP Cover title. "September 2007"--P. [2] of cover. For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from [the square root of n]-consistent estimators may be used in place of efficient solutions of the likelihood equations in likelihood ratio, Wald, and Rao tests. Taking a quadratic mean differentiability approach, Lehmann and Romano have outlined proofs of similar results. We take a Cramér condition approach and make the conditions and their use explicit. Keywords: coefficient of variation, signal to noise ratio, risk to return ratio, one-step Newton estimators, Newton's method, [the square root of n]-consistent estimators, efficient likelihood estimators, Cramér conditions, quadratic mean differentiability, likelihood ratio test, Wald test, Rao test, asymptotics. Statistical hypothesis testing Asymptotic theory Confidence intervals |
| title | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_author | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_author_exact | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_browse | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_browse_sort | Confidence bounds and hypothesis tests for normal distribution coefficients of variation |
| title_full | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_fullStr | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_full_exact | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_full_unstemmed | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_short | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_short_exact | Confidence bounds and hypothesis tests for normal distribution coefficients of variation / |
| title_sort | confidence bounds and hypothesis tests for normal distribution coefficients of variation |
| topic | Statistical hypothesis testing Asymptotic theory Confidence intervals |
| topic_browse | Statistical Hypothesis Testing Asymptotic Theory Confidence Intervals |
| url | http://www.fpl.fs.fed.us/documnts/fplrp/fpl_rp638.pdf |