menu
{ "item_title" : "Quantile Regression for Cross-Sectional and Time Series Data", "item_author" : [" Jorge M. Uribe", "Montserrat Guillen "], "item_description" : "This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit students using the methodology for the first time, and practitioners at private or public organizations who are interested in modeling different fragments of the conditional distribution of a given variable. The book pursues a practical approach with reference to energy markets, helping readers learn the main features of the technique more quickly. Emphasis is placed on the implementation details and the correct interpretation of the quantile regression coefficients rather than on the technicalities of the method, unlike the approach used in the majority of the literature. All applications are illustrated with R.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/044/503/3030445038_b.jpg", "price_data" : { "retail_price" : "69.99", "online_price" : "69.99", "our_price" : "69.99", "club_price" : "69.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Quantile Regression for Cross-Sectional and Time Series Data|Jorge M. Uribe

Quantile Regression for Cross-Sectional and Time Series Data : Applications in Energy Markets Using R

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit students using the methodology for the first time, and practitioners at private or public organizations who are interested in modeling different fragments of the conditional distribution of a given variable. The book pursues a practical approach with reference to energy markets, helping readers learn the main features of the technique more quickly. Emphasis is placed on the implementation details and the correct interpretation of the quantile regression coefficients rather than on the technicalities of the method, unlike the approach used in the majority of the literature. All applications are illustrated with R.



This item is Non-Returnable

Details

  • ISBN-13: 9783030445034
  • ISBN-10: 3030445038
  • Publisher: Springer
  • Publish Date: March 2020
  • Dimensions: 9.21 x 6.14 x 0.16 inches
  • Shipping Weight: 0.26 pounds
  • Page Count: 63

Related Categories

You May Also Like...

    1

BAM Customer Reviews