Quantile Regression for Cross-Sectional and Time Series Data: Applications in Energy Markets Using R.
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cham
Springer International Publishing AG
2020
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Schriftenreihe: | SpringerBriefs in Finance Ser
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Schlagworte: | |
Beschreibung: | Description based on publisher supplied metadata and other sources |
Beschreibung: | 1 Online-Ressource (67 pages) |
ISBN: | 9783030445041 |
Internformat
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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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Datensatz im Suchindex
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adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
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 |
bvnumber | BV048222602 |
collection | ZDB-30-PQE |
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 |
discipline_str_mv | Mathematik |
format | Electronic eBook |
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illustrated | Not Illustrated |
index_date | 2024-07-03T19:50:37Z |
indexdate | 2024-07-10T09:32:26Z |
institution | BVB |
isbn | 9783030445041 |
language | English |
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publisher | Springer International Publishing AG |
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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_exact_search_txtP | 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 |