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Local Regression and Likelihood [electronic resource] /
Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.
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| Format: | Texto biblioteca |
| Language: | eng |
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New York, NY : Springer New York,
1999
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| Subjects: | Mathematics., Economics, Mathematical., Probabilities., Statistics., Probability Theory and Stochastic Processes., Statistics and Computing/Statistics Programs., Statistics for Business/Economics/Mathematical Finance/Insurance., Quantitative Finance., |
| Online Access: | http://dx.doi.org/10.1007/b98858 |
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KOHA-OAI-TEST:2180002018-07-30T23:54:14ZLocal Regression and Likelihood [electronic resource] / Loader, Clive. author. SpringerLink (Online service) textNew York, NY : Springer New York,1999.engSeparation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.The Origins of Local Regression -- Local Regression Methods -- Fitting with LOCFIT -- Local Likelihood Estimation -- Density Estimation -- Flexible Local Regression -- Survival and Failure Time Analysis -- Discrimination and Classification -- Variance Estimation and Goodness of Fit -- Bandwidth Selection -- Adaptive Parameter Choice -- Computational Methods -- Optimizing Local Regression.Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.Mathematics.Economics, Mathematical.Probabilities.Statistics.Mathematics.Probability Theory and Stochastic Processes.Statistics and Computing/Statistics Programs.Statistics for Business/Economics/Mathematical Finance/Insurance.Quantitative Finance.Springer eBookshttp://dx.doi.org/10.1007/b98858URN:ISBN:9780387227320 |
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COLPOS |
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México |
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MX |
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cat-colpos |
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biblioteca |
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America del Norte |
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Departamento de documentación y biblioteca de COLPOS |
| language |
eng |
| topic |
Mathematics. Economics, Mathematical. Probabilities. Statistics. Mathematics. Probability Theory and Stochastic Processes. Statistics and Computing/Statistics Programs. Statistics for Business/Economics/Mathematical Finance/Insurance. Quantitative Finance. Mathematics. Economics, Mathematical. Probabilities. Statistics. Mathematics. Probability Theory and Stochastic Processes. Statistics and Computing/Statistics Programs. Statistics for Business/Economics/Mathematical Finance/Insurance. Quantitative Finance. |
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Mathematics. Economics, Mathematical. Probabilities. Statistics. Mathematics. Probability Theory and Stochastic Processes. Statistics and Computing/Statistics Programs. Statistics for Business/Economics/Mathematical Finance/Insurance. Quantitative Finance. Mathematics. Economics, Mathematical. Probabilities. Statistics. Mathematics. Probability Theory and Stochastic Processes. Statistics and Computing/Statistics Programs. Statistics for Business/Economics/Mathematical Finance/Insurance. Quantitative Finance. Loader, Clive. author. SpringerLink (Online service) Local Regression and Likelihood [electronic resource] / |
| description |
Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software. |
| format |
Texto |
| topic_facet |
Mathematics. Economics, Mathematical. Probabilities. Statistics. Mathematics. Probability Theory and Stochastic Processes. Statistics and Computing/Statistics Programs. Statistics for Business/Economics/Mathematical Finance/Insurance. Quantitative Finance. |
| author |
Loader, Clive. author. SpringerLink (Online service) |
| author_facet |
Loader, Clive. author. SpringerLink (Online service) |
| author_sort |
Loader, Clive. author. |
| title |
Local Regression and Likelihood [electronic resource] / |
| title_short |
Local Regression and Likelihood [electronic resource] / |
| title_full |
Local Regression and Likelihood [electronic resource] / |
| title_fullStr |
Local Regression and Likelihood [electronic resource] / |
| title_full_unstemmed |
Local Regression and Likelihood [electronic resource] / |
| title_sort |
local regression and likelihood [electronic resource] / |
| publisher |
New York, NY : Springer New York, |
| publishDate |
1999 |
| url |
http://dx.doi.org/10.1007/b98858 |
| work_keys_str_mv |
AT loadercliveauthor localregressionandlikelihoodelectronicresource AT springerlinkonlineservice localregressionandlikelihoodelectronicresource |
| _version_ |
1756269829538447360 |