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Computational considerations in functional principal component analysis
Ocaña, Francisco; Aguilera, Ana; Escabias, Manuel - In: Computational Statistics 22 (2007) 3, pp. 449-465
Persistent link: https://www.econbiz.de/10005166798
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Estimating value at risk with semiparametric support vector quantile regression
Shim, Jooyong; Kim, Yongtae; Lee, Jangtaek; Hwang, Changha - In: Computational Statistics 27 (2012) 4, pp. 685-700
Value at Risk (VaR) has been used as an important tool to measure the market risk under normal market. Usually the VaR of log returns is calculated by assuming a normal distribution. However, log returns are frequently found not normally distributed. This paper proposes the estimation approach...
Persistent link: https://www.econbiz.de/10010847975
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Inferring Boolean functions via higher-order correlations
Maucher, Markus; Kracht, David; Schober, Steffen; … - In: Computational Statistics 29 (2014) 1, pp. 97-115
dependency between variables, but are also more sensitive to noise. Furthermore computational complexity increases exponentially … equivalent for the reconstruction of Boolean functions. Secondly, we also investigate under which conditions (noise, number of …
Persistent link: https://www.econbiz.de/10010847673