000 | 02382nam a2200301Ia 4500 | ||
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001 | 355562 | ||
003 | 0000000000 | ||
005 | 20211104093408.0 | ||
008 | 180629s2018 nju 000 0 eng c | ||
010 | _a2018023718 | ||
020 | _a9781119431909 (hardcover) | ||
035 | _a20566778 | ||
040 |
_aWaSeSS/DLC _cWaSeSS _erda |
||
050 |
_aQA 280 _b.P196 2019 |
||
100 |
_aPaolella, Marc S., _9128246 |
||
245 | 0 |
_aLinear models and time-series analysis : _bregression, ANOVA, ARMA and GARCH / _cDr. Marc S. Paolella. |
|
264 |
_aHoboken, NJ : _bJohn Wiley & Sons, _cc2019. |
||
300 |
_axvi, 880 pages _c24 cm. |
||
336 |
_atext _2rdacontent |
||
337 |
_aunmediated _2rdamedia |
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338 |
_avolume _2rdacarrier |
||
520 | _aA comprehensive and timely edition on an emerging new trend in time series. Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. --Wiley.com | ||
650 |
_aLinear models (Statistics) _953804 |
||
650 |
_aTime-series analysis. _929980 |
||
942 | _cCIR | ||
999 |
_c91918 _d91918 |