000			01519nam a22002177a 4500
999			_c4106 _d4106
005			20221111133349.0
008			221111b ||||| |||| 00| 0 eng d
020			_a9783030445034
082			_a519.536 _bURI
100			_aUribe, Jorge M. _99310
245			_aQuantile regression for cross-sectional and time series data
260			_aSpringer _bSwitzerland _c2020
300			_ax, 63 p.
365			_aEURO _b27.99
520			_aAbout this book 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.
650			_aR (Computer program language) _91512
650			_aTime-series analysis _9176
650			_aQuantile regression _99949
700			_aGuillen, Montserrat _99950
942			_2ddc _cBK