“…In the third case, the distribution and the moments of the square of the norm are obtained from the density of the norm W which is given in Mathai et al [26], Section 3.2. Additional results on the moments of sample serial covariances may be found for example in Provost and Rudiuk [28] and Sutradhar [30] for the Gaussian case.…”
Section: Application To the Sample Serial Covariancementioning
confidence: 96%
“…As an example, one may take the lag-k sample serial correlation coefficient, that is, P k ( yÄ )ÂP 0 ( yÄ ), with P k ( yÄ )=(y$VA k V y)ÂT according to (28), noting that P 0 ( yÄ )=(y$V y)ÂT and V is idempotent.…”
This paper provides computable representations for the evaluation of the probability content of cones in isotropic random fields. A decomposition of quadratic forms in spherically symmetric random vectors is obtained and a representation of their moments is derived in terms of finite sums. These results are combined to obtain the distribution function of quadratic forms in spherically symmetric or central elliptically contoured random vectors. Some numerical examples involving the sample serial covariance are provided. Ratios of quadratic forms are also discussed.
1998Academic Press
“…In the third case, the distribution and the moments of the square of the norm are obtained from the density of the norm W which is given in Mathai et al [26], Section 3.2. Additional results on the moments of sample serial covariances may be found for example in Provost and Rudiuk [28] and Sutradhar [30] for the Gaussian case.…”
Section: Application To the Sample Serial Covariancementioning
confidence: 96%
“…As an example, one may take the lag-k sample serial correlation coefficient, that is, P k ( yÄ )ÂP 0 ( yÄ ), with P k ( yÄ )=(y$VA k V y)ÂT according to (28), noting that P 0 ( yÄ )=(y$V y)ÂT and V is idempotent.…”
This paper provides computable representations for the evaluation of the probability content of cones in isotropic random fields. A decomposition of quadratic forms in spherically symmetric random vectors is obtained and a representation of their moments is derived in terms of finite sums. These results are combined to obtain the distribution function of quadratic forms in spherically symmetric or central elliptically contoured random vectors. Some numerical examples involving the sample serial covariance are provided. Ratios of quadratic forms are also discussed.
1998Academic Press
“…Although this exact distribution is well known (see Ali (1984) and Provost and Rudiuk (1995)), its practical use has been very limited. The main obstacle in its computation is obtaining the eigenvalues of a symmetric n × n matrix, where n is the length of the time series.…”
“…Such ratios arise for example in regression and analysis of variance problems associated with linear models. The sample serial correlation coeËficient as defined in Anderson (1990) and discussed in Provost and Rudiuk (1995) also has this structure.…”
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