000			03592nam a22003615i 4500
001			102601
003			DE-He213
005			20240111050141.0
007			cr nn 008mamaa
008			171201s2018 gw | s |||| 0|eng d
020			_a9783319709420
024	7		_a10.1007/978-3-319-70942-0 _2doi
050		4	_aHB139 _b.P743 2018 EB
245	1	0	_aPredictive Econometrics and Big Data _cedited by Vladik Kreinovich, Songsak Sriboonchitta, Nopasit Chakpitak.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XII, 780 páginas 146 ilustraciones)
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v753
505	0		_aData in the 21st Century -- The Understanding of Dependent Structure and Co-Movement of World Stock Exchanges Under the Economic Cycle -- Macro-Econometric Forecasting for During Periods of Economic Cycle Using Bayesian Extreme Value Optimization Algorithm -- Generalize Weighted in Interval Data for Fitting a Vector Autoregressive Model -- Asymmetric Effect with Quantile Regression for Interval-valued Variables -- Emissions, Trade Openness, Urbanisation, and Income in Thailand: An Empirical Analysis -- Does Forecasting Benefit from Mixed-Frequency Data Sampling Model: The Evidence from Forecasting GDP Growth Using Financial Factor in Thailand -- How Better Are Predictive Models: Analysis on the Practically Important Example of Robust Interval Uncertainty.
520	3		_aThis book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques - which directly aim at predicting economic phenomena; and big data techniques - which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
650		7	_aEconometría _2embne _9405121
650		7	_aInteligencia artificial _2embne _9413115
700	1		_aKreinovich, Vladik _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n95102697 _1http://viaf.org/viaf/37212054/ _998177
700	1		_aSongsak Sriboonchitta _0http://id.loc.gov/authorities/names/n88194015 _1http://viaf.org/viaf/18781043/
700	1		_aChakpitak, Nopasit. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _1http://viaf.org/viaf/210336485/
776	0	8	_iEdición impresa: _z9783319709413
776	0	8	_iEdición impresa: _z9783319709437
776	0	8	_iEdición impresa: _z9783319890180
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-70942-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b12/2018 _dz _ek _feng _ggw _h0
999			_c102601 _d102601 _x1