gloomy
发表于 2025-3-21 17:58:47
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Hyperlipidemia
发表于 2025-3-21 23:56:24
1431-875X lied to financial problems.May be used as textbook in advanc.Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing fi
Judicious
发表于 2025-3-22 01:32:28
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共同给与
发表于 2025-3-22 08:39:01
Dependence & Multivariate Data Exploration the normal or Gaussian distribution. For jointly Gaussian random variables, dependence can be completely captured by the classical Pearson correlation coefficient. In general however, the situation can be quite different.
包庇
发表于 2025-3-22 11:15:49
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Transfusion
发表于 2025-3-22 13:37:32
Multivariate Time Series, Linear Systems and Kalman Filteringtion, because of its increased popularity and its tremendous potential, we decided to include this alternative approach in this chapter. The tone of the chapter will have to change slightly as we discuss concepts and theories which were introduced and developed in engineering fields far remote from financial applications.
Ferritin
发表于 2025-3-22 19:11:11
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inveigh
发表于 2025-3-22 21:33:40
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malapropism
发表于 2025-3-23 03:31:46
Heavy Tail Distributionsresults underpinning the estimation of the probabilities of these extreme and rare events. The basics of extreme value theory are presented as they pertain to estimation and risk management of extremes observed in financial applications.
Panther
发表于 2025-3-23 07:13:08
Dependence & Multivariate Data Exploration, we discuss multivariate versions of kernel density estimators. Then we review the properties of the most important multivariate distribution of all, the normal or Gaussian distribution. For jointly Gaussian random variables, dependence can be completely captured by the classical Pearson correlatio