Multivariate continuous probability distributions and partial differential equationsA simple and nice connection . .
- Julia Calatayud Gregori
- Juan Carlos Cortés López
- Marc Jornet Sanz
ISSN: 1889-3805
Année de publication: 2018
Volumen: 34
Número: 2
Pages: 149-158
Type: Article
D'autres publications dans: BEIO, Boletín de Estadística e Investigación Operativa
Références bibliographiques
- [1] Cort ́es J.-C., Navarro A., S ́anchez A., y Calbo G. (2016). Distribuciones deprobabilidad continuas y ecuaciones diferenciales ordinarias.Bol. Soc. PuigAdam,101, 42–49.
- [2] Kotz S., Balakrishnan N., y Johnson N.L. (2000).Continuous MultivariateDistributions, Volume 1: Models and Applications, Second edition, Wiley,New York (USA).
- [3] Lee C., Famoye F., y Alzaatreh A.Y. (2013). Methods for generating familiesof univariate continuous distributions in the recent decades.WIREs Comput.Stat.,5, 219–238, Doi: 10.1002/wics.1255.
- [4] Pal S., y Murthy G.S.R. (2003). An application of Gumbel’s bivariate expo-nential distribution in estimation of warranty cost of motor cycles.Int. J.Qual. Reliab. Manag.,20(4), 48–502, Doi: 10.1108/02656710310468650.
- [5] Pearson K. (1985). Contributions to the mathematical theory of evolution,II: Skew variation in homogeneous material.Phil. Trans. Royal Soc.,186,343–414, Doi: 10.1098/rsta.1895.0010.
- [6] Smith P.J. (2002).Analysis of Failure and Survival Data, Chapman andHall, New York (USA)
- [7] Villanueva D., Feij ́oo A., y Pazos J.L. (2013). Multivariate Weibull Distri-bution for Wind Speed and Wind Power Behavior Assessment.Resour.,2,370–384, Doi: 10.3390/resources20303