In this paper. we derive the moments of random vectors with multivariate skew-normal distribution and their quadratic forms. Applications to time series and spatial statistics are discussed. In particular, it is shown that the moments of the sample autocovariance function and of the sample variogram estimator do not depend on the skewness vector. (C) 2001 Elsevier Science B.V. All rights reserved.
机构:
Hangzhou Dianzi Univ, Coll Econ, Hangzhou, Peoples R ChinaHangzhou Dianzi Univ, Coll Econ, Hangzhou, Peoples R China
Ye, Rendao
Wang, Tonghui
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Northwest A & F Univ, Innovat Expt Coll, Yangling, Peoples R China
New Mexico State Univ, Dept Math Sci, Las Cruces, NM 88003 USAHangzhou Dianzi Univ, Coll Econ, Hangzhou, Peoples R China
Wang, Tonghui
Gupta, Arjun K.
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Bowling Green State Univ, Dept Math & Stat, Bowling Green, OH 43403 USAHangzhou Dianzi Univ, Coll Econ, Hangzhou, Peoples R China
机构:
E Tennessee State Univ, Dept Biostat & Epidemiol, Inst Quantitat Biol, Box 70259, Johnson City, TN 37614 USA
Nanjing Audit Univ, Dept Finance, Nanjing, Jiangsu, Peoples R ChinaE Tennessee State Univ, Dept Biostat & Epidemiol, Inst Quantitat Biol, Box 70259, Johnson City, TN 37614 USA
Zheng, Shimin
Knisley, Jeff
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E Tennessee State Univ, Dept Math & Stat, Inst Quantitat Biol, Johnson City, TN 37614 USAE Tennessee State Univ, Dept Biostat & Epidemiol, Inst Quantitat Biol, Box 70259, Johnson City, TN 37614 USA
Knisley, Jeff
Wang, Kesheng
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E Tennessee State Univ, Dept Biostat & Epidemiol, Inst Quantitat Biol, Box 70259, Johnson City, TN 37614 USAE Tennessee State Univ, Dept Biostat & Epidemiol, Inst Quantitat Biol, Box 70259, Johnson City, TN 37614 USA