Quantile Regression for Cross-Sectional and Time Series Data: Applications in Energy Markets Using R.
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2020
|
| Schriftenreihe: | SpringerBriefs in Finance Ser
|
| Schlagwörter: | |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Umfang: | 1 Online-Ressource (67 pages) |
| ISBN: | 9783030445041 |
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| 100 | 1 | |a Uribe, Jorge M. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Quantile Regression for Cross-Sectional and Time Series Data |b Applications in Energy Markets Using R. |
| 264 | 1 | |a Cham |b Springer International Publishing AG |c 2020 | |
| 264 | 4 | |c ©2020 | |
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| 505 | 8 | |a Intro -- Preface -- About This Book -- Contents -- 1 Why and When Should Quantile Regression Be Used? -- References -- 2 A Case Study: Modeling Energy Markets by the Means of Quantile Regression -- 2.1 Energy Markets -- 2.2 Energy and Quantile Regression: An Overview of Existing Analysis -- References -- 3 Quantile Regression: A Methodological Overview -- 3.1 Definition of Quantile and Conditional Quantile -- 3.2 Estimating the Quantile in the Univariate Case -- 3.3 Quantile Regression Estimation -- 3.4 Quantile Regression Estimation Versus Weighted Quantile Regression Estimation -- References -- 4 Cross-sectional Quantile Regression -- 4.1 Data Source -- 4.2 Weighted Versus Unweighted Linear Regression: A Simple Example -- 4.3 Quantile Regression in a Simple One-Covariate Model -- 4.4 Coefficient Interpretation -- 4.5 Quantile Regression in a Multiple-Covariate Model -- 4.6 Conditional Versus Unconditional Quantile Regression -- 4.7 Summarizing Remarks -- References -- 5 Time Series Quantile Regression -- 5.1 Data Source -- 5.2 Natural Gas Prices as a Determinant of Electricity Prices-An OLS Example -- 5.3 Quantile Regression in a Simple One-Covariate Model -- 5.4 Coefficient Interpretation -- 5.5 Autoregressive Quantiles -- 5.6 Summarizing Remarks -- Reference -- 6 Goodness of Fit in Quantile Regression Models -- Reference -- 7 Novel Approaches in Quantile Regression -- 7.1 Nonparametric Quantile Regression -- 7.2 The Cross-Quantilogram for Time Series -- 7.2.1 The Cross-Quantilogram Definition -- 7.2.2 Q-Test for Directional Predictability -- 7.2.3 The Stationary Bootstrap -- 7.3 Quantile Regression Forests -- References -- 8 What Have We Learned from Quantile Regression? Implications for Economics and Finance -- Appendix Programs for Quantile Regression and Implementation in R. | |
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| 912 | |a ZDB-30-PQE | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-033603335 | |
Datensatz im Suchindex
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| author | Uribe, Jorge M. |
| author_facet | Uribe, Jorge M. |
| author_role | aut |
| author_sort | Uribe, Jorge M. |
| author_variant | j m u jm jmu |
| building | Verbundindex |
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| contents | Intro -- Preface -- About This Book -- Contents -- 1 Why and When Should Quantile Regression Be Used? -- References -- 2 A Case Study: Modeling Energy Markets by the Means of Quantile Regression -- 2.1 Energy Markets -- 2.2 Energy and Quantile Regression: An Overview of Existing Analysis -- References -- 3 Quantile Regression: A Methodological Overview -- 3.1 Definition of Quantile and Conditional Quantile -- 3.2 Estimating the Quantile in the Univariate Case -- 3.3 Quantile Regression Estimation -- 3.4 Quantile Regression Estimation Versus Weighted Quantile Regression Estimation -- References -- 4 Cross-sectional Quantile Regression -- 4.1 Data Source -- 4.2 Weighted Versus Unweighted Linear Regression: A Simple Example -- 4.3 Quantile Regression in a Simple One-Covariate Model -- 4.4 Coefficient Interpretation -- 4.5 Quantile Regression in a Multiple-Covariate Model -- 4.6 Conditional Versus Unconditional Quantile Regression -- 4.7 Summarizing Remarks -- References -- 5 Time Series Quantile Regression -- 5.1 Data Source -- 5.2 Natural Gas Prices as a Determinant of Electricity Prices-An OLS Example -- 5.3 Quantile Regression in a Simple One-Covariate Model -- 5.4 Coefficient Interpretation -- 5.5 Autoregressive Quantiles -- 5.6 Summarizing Remarks -- Reference -- 6 Goodness of Fit in Quantile Regression Models -- Reference -- 7 Novel Approaches in Quantile Regression -- 7.1 Nonparametric Quantile Regression -- 7.2 The Cross-Quantilogram for Time Series -- 7.2.1 The Cross-Quantilogram Definition -- 7.2.2 Q-Test for Directional Predictability -- 7.2.3 The Stationary Bootstrap -- 7.3 Quantile Regression Forests -- References -- 8 What Have We Learned from Quantile Regression? Implications for Economics and Finance -- Appendix Programs for Quantile Regression and Implementation in R. |
| ctrlnum | (ZDB-30-PQE)EBC6151482 (ZDB-30-PAD)EBC6151482 (ZDB-89-EBL)EBL6151482 (OCoLC)1148207609 (DE-599)BVBBV048222602 |
| dewey-full | 519.53599999999994 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.53599999999994 |
| dewey-search | 519.53599999999994 |
| dewey-sort | 3519.53599999999994 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | DE-604.BV048222602 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:38:56Z |
| institution | BVB |
| isbn | 9783030445041 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033603335 |
| oclc_num | 1148207609 |
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| physical | 1 Online-Ressource (67 pages) |
| psigel | ZDB-30-PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer International Publishing AG |
| record_format | marc |
| series2 | SpringerBriefs in Finance Ser |
| spelling | Uribe, Jorge M. Verfasser aut Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. Cham Springer International Publishing AG 2020 ©2020 1 Online-Ressource (67 pages) txt rdacontent c rdamedia cr rdacarrier SpringerBriefs in Finance Ser Description based on publisher supplied metadata and other sources Intro -- Preface -- About This Book -- Contents -- 1 Why and When Should Quantile Regression Be Used? -- References -- 2 A Case Study: Modeling Energy Markets by the Means of Quantile Regression -- 2.1 Energy Markets -- 2.2 Energy and Quantile Regression: An Overview of Existing Analysis -- References -- 3 Quantile Regression: A Methodological Overview -- 3.1 Definition of Quantile and Conditional Quantile -- 3.2 Estimating the Quantile in the Univariate Case -- 3.3 Quantile Regression Estimation -- 3.4 Quantile Regression Estimation Versus Weighted Quantile Regression Estimation -- References -- 4 Cross-sectional Quantile Regression -- 4.1 Data Source -- 4.2 Weighted Versus Unweighted Linear Regression: A Simple Example -- 4.3 Quantile Regression in a Simple One-Covariate Model -- 4.4 Coefficient Interpretation -- 4.5 Quantile Regression in a Multiple-Covariate Model -- 4.6 Conditional Versus Unconditional Quantile Regression -- 4.7 Summarizing Remarks -- References -- 5 Time Series Quantile Regression -- 5.1 Data Source -- 5.2 Natural Gas Prices as a Determinant of Electricity Prices-An OLS Example -- 5.3 Quantile Regression in a Simple One-Covariate Model -- 5.4 Coefficient Interpretation -- 5.5 Autoregressive Quantiles -- 5.6 Summarizing Remarks -- Reference -- 6 Goodness of Fit in Quantile Regression Models -- Reference -- 7 Novel Approaches in Quantile Regression -- 7.1 Nonparametric Quantile Regression -- 7.2 The Cross-Quantilogram for Time Series -- 7.2.1 The Cross-Quantilogram Definition -- 7.2.2 Q-Test for Directional Predictability -- 7.2.3 The Stationary Bootstrap -- 7.3 Quantile Regression Forests -- References -- 8 What Have We Learned from Quantile Regression? Implications for Economics and Finance -- Appendix Programs for Quantile Regression and Implementation in R. Quantile regression Guillen, Montserrat Sonstige oth Erscheint auch als Druck-Ausgabe Uribe, Jorge M. Quantile Regression for Cross-Sectional and Time Series Data Cham : Springer International Publishing AG,c2020 9783030445034 |
| spellingShingle | Uribe, Jorge M. Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. Intro -- Preface -- About This Book -- Contents -- 1 Why and When Should Quantile Regression Be Used? -- References -- 2 A Case Study: Modeling Energy Markets by the Means of Quantile Regression -- 2.1 Energy Markets -- 2.2 Energy and Quantile Regression: An Overview of Existing Analysis -- References -- 3 Quantile Regression: A Methodological Overview -- 3.1 Definition of Quantile and Conditional Quantile -- 3.2 Estimating the Quantile in the Univariate Case -- 3.3 Quantile Regression Estimation -- 3.4 Quantile Regression Estimation Versus Weighted Quantile Regression Estimation -- References -- 4 Cross-sectional Quantile Regression -- 4.1 Data Source -- 4.2 Weighted Versus Unweighted Linear Regression: A Simple Example -- 4.3 Quantile Regression in a Simple One-Covariate Model -- 4.4 Coefficient Interpretation -- 4.5 Quantile Regression in a Multiple-Covariate Model -- 4.6 Conditional Versus Unconditional Quantile Regression -- 4.7 Summarizing Remarks -- References -- 5 Time Series Quantile Regression -- 5.1 Data Source -- 5.2 Natural Gas Prices as a Determinant of Electricity Prices-An OLS Example -- 5.3 Quantile Regression in a Simple One-Covariate Model -- 5.4 Coefficient Interpretation -- 5.5 Autoregressive Quantiles -- 5.6 Summarizing Remarks -- Reference -- 6 Goodness of Fit in Quantile Regression Models -- Reference -- 7 Novel Approaches in Quantile Regression -- 7.1 Nonparametric Quantile Regression -- 7.2 The Cross-Quantilogram for Time Series -- 7.2.1 The Cross-Quantilogram Definition -- 7.2.2 Q-Test for Directional Predictability -- 7.2.3 The Stationary Bootstrap -- 7.3 Quantile Regression Forests -- References -- 8 What Have We Learned from Quantile Regression? Implications for Economics and Finance -- Appendix Programs for Quantile Regression and Implementation in R. Quantile regression |
| title | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_auth | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_exact_search | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_full | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_fullStr | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_full_unstemmed | Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R. |
| title_short | Quantile Regression for Cross-Sectional and Time Series Data |
| title_sort | quantile regression for cross sectional and time series data applications in energy markets using r |
| title_sub | Applications in Energy Markets Using R. |
| topic | Quantile regression |
| topic_facet | Quantile regression |
| work_keys_str_mv | AT uribejorgem quantileregressionforcrosssectionalandtimeseriesdataapplicationsinenergymarketsusingr AT guillenmontserrat quantileregressionforcrosssectionalandtimeseriesdataapplicationsinenergymarketsusingr |