(Kotz, Balakrishnan, and Johnson 2000, 451)
(Gunst and Webster 1973)
(Amos and Bulgren 1972)
let (q,,q2) ~iv%’(ab,, c) denote that the random
ldariab!es q, am! q 2 have a hivariate Chi-square distribution, where
a = degrees of freedom of rhe marginai Chi-square distribution of ql,
6 = &,geesof fr~edorni;f the rnargica! CEi-square distribution ofqz,
c = number of non-zero canonical correlations between the underlying nmmz! vectors of qi and qi.
Qui-quadrado multivariada (Jensen)
(Kotz, Balakrishnan, and Johnson 2000, 471)
“The joint distribution of \(Y_1,\ldots,Y_k\) can be regarded as a multivariate chi-squared or, more generally (allowing \(\nu\) and the \(p_j\)’s to take fractional values), a multivariate gamma distribution.” (Kotz, Balakrishnan, and Johnson 2000, 474)
Amos, DE, and WG Bulgren. 1972. “Computation of a Multivariate f Distribution.” Mathematics of Computation
26 (117): 255–64. https://www.ams.org/journals/mcom/1972-26-117/S0025-5718-1972-0298881-9/S0025-5718-1972-0298881-9.pdf
Gunst, Richard F, and John T Webster. 1973. “Density Functions of the Bivariate Chi-Square Distribution.” Journal of Statistical Computation and Simulation
2 (3): 275–88. http://dx.doi.org/10.1080/00949657308810052
Kotz, Samuel, N Balakrishnan, and Norman L Johnson. 2000. “Continuous Multivariate Distributions. Vol. 1. Models and Applications.” Wiley-Interscience, New York.