The generalized method of moments as applied to the generalized gamma distribution
| ISSN: |
1436-3259
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| Keywords: |
Floods ; estimation ; quantiles ; generalized gamma ; generalized moments ; standard error
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| Source: |
Springer Online Journal Archives 1860-2000
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| Topics: |
Architecture, Civil Engineering, Surveying
Energy, Environment Protection, Nuclear Power Engineering
Geography
Geosciences
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| Notes: |
Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest.
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| Type of Medium: |
Electronic Resource
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| URL: |
| _version_ | 1798296238372683776 |
|---|---|
| autor | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| autorsonst | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| book_url | http://dx.doi.org/10.1007/BF01550839 |
| datenlieferant | nat_lic_papers |
| hauptsatz | hsatz_simple |
| identnr | NLM205975933 |
| issn | 1436-3259 |
| journal_name | Stochastic environmental research and risk assessment |
| materialart | 1 |
| notes | Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest. |
| package_name | Springer |
| publikationsjahr_anzeige | 1988 |
| publikationsjahr_facette | 1988 |
| publikationsjahr_intervall | 8014:1985-1989 |
| publikationsjahr_sort | 1988 |
| publisher | Springer |
| reference | 2 (1988), S. 161-174 |
| schlagwort | Floods estimation quantiles generalized gamma generalized moments standard error |
| search_space | articles |
| shingle_author_1 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| shingle_author_2 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| shingle_author_3 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| shingle_author_4 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. |
| shingle_catch_all_1 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. The generalized method of moments as applied to the generalized gamma distribution Floods estimation quantiles generalized gamma generalized moments standard error Floods estimation quantiles generalized gamma generalized moments standard error Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest. 1436-3259 14363259 Springer |
| shingle_catch_all_2 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. The generalized method of moments as applied to the generalized gamma distribution Floods estimation quantiles generalized gamma generalized moments standard error Floods estimation quantiles generalized gamma generalized moments standard error Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest. 1436-3259 14363259 Springer |
| shingle_catch_all_3 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. The generalized method of moments as applied to the generalized gamma distribution Floods estimation quantiles generalized gamma generalized moments standard error Floods estimation quantiles generalized gamma generalized moments standard error Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest. 1436-3259 14363259 Springer |
| shingle_catch_all_4 | Ashkar, F. Bobée, B. Leroux, D. Morisette, D. The generalized method of moments as applied to the generalized gamma distribution Floods estimation quantiles generalized gamma generalized moments standard error Floods estimation quantiles generalized gamma generalized moments standard error Abstract The generalized gamma (GG) distribution has a density function that can take on many possible forms commonly encountered in hydrologic applications. This fact has led many authors to study the properties of the distribution and to propose various estimation techniques (method of moments, mixed moments, maximum likelihood etc.). We discuss some of the most important properties of this flexible distribution and present a flexible method of parameter estimation, called the “generalized method of moments” (GMM) which combines any three moments of the GG distribution. The main advantage of this general method is that it has many of the previously proposed methods of estimation as special cases. We also give a general formula for the variance of theT-year eventX T obtained by the GMM along with a general formula for the parameter estimates and also for the covariances and correlation coefficients between any pair of such estimates. By applying the GMM and carefully choosing the order of the moments that are used in the estimation one can significantly reduce the variance ofT-year events for the range of return periods that are of interest. 1436-3259 14363259 Springer |
| shingle_title_1 | The generalized method of moments as applied to the generalized gamma distribution |
| shingle_title_2 | The generalized method of moments as applied to the generalized gamma distribution |
| shingle_title_3 | The generalized method of moments as applied to the generalized gamma distribution |
| shingle_title_4 | The generalized method of moments as applied to the generalized gamma distribution |
| sigel_instance_filter | dkfz geomar wilbert ipn albert fhp |
| source_archive | Springer Online Journal Archives 1860-2000 |
| timestamp | 2024-05-06T09:48:55.494Z |
| titel | The generalized method of moments as applied to the generalized gamma distribution |
| titel_suche | The generalized method of moments as applied to the generalized gamma distribution |
| topic | ZH-ZI ZP R TE-TZ |
| uid | nat_lic_papers_NLM205975933 |