Un programa gauss para simular distribuciones no normales multivariadas

  1. San Luis Costas, Concepción
  2. Sánchez Bruno, Juan Alfonso
  3. Hernández Cabrera, Juan Andrés
Revue:
Psicothema

ISSN: 0214-9915

Année de publication: 1995

Volumen: 7

Número: 2

Pages: 427-434

Type: Article

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D'autres publications dans: Psicothema

Résumé

Se presenta dos programas en GAUSS, que permite generar muestras de tamaño n y p variables con características de distribución en asimetría y apuntamiento definidos previamente por el usuario, a partir de la matriz de correlaciones de las variables implicadas, en base a los algoritmos de Fleishman (1978) y Vale y Maurelli (1983).

Références bibliographiques

  • Boomsma, A. (1983). On the robustness of LISREL (maximum likelihood estimation) against small sample size and nonnormality. Unpublished PhD dissertation, University of Groningen, Groningen. The Netherlands.
  • Babakus, E., Ferguson, C.E., & Joreskog, K.G. (1987). The sensitivity of Confirmatory Maximum likelihood factor analysis to violations of measurement scale and distributional assumptions. Journal of Marketing Research. 24, 222-228.
  • Chou, C.E, Bentler, P.M. & Satorra, A. (1991). Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: A Monte Carlo study. British Journal of Mathematical and Statistical Psychology, 44, 47-357.
  • Fleishman, A.(1978). A method for simulating non-normal distributions. Psychometrika, 43, 4, 521-531.
  • Gauss Sistem Version 3.0. Aptech Systems, Inc.
  • Sharma, S., Durvasula, S. & Dillon, W.R. (1989). Some results on the behavior of alternate covariance structure estimation procedures in the presence on non-normal data. Journal of Marketing Research, 26, 214-221.
  • Vale, D. & Maurelli, V. (1983). Simulating multivariate nonnormal distributions. Psychometrika, 48, 3, 465-471.
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