Pitman efficiencies of -goodness-of-fit tests
Jan Beirlant, László Györfi (1994)
Kybernetika
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Jan Beirlant, László Györfi (1994)
Kybernetika
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Teresa Pérez, Julio A. Pardo (2003)
Kybernetika
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In this paper a new family of statistics based on -divergence for testing goodness-of-fit under composite null hypotheses are considered. The asymptotic distribution of this test is obtained when the unspecified parameters are estimated by maximum likelihood as well as minimum -divergence.
Antonio Dorival Campos (1987)
Trabajos de Estadística
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By analogy to the real case established by Matusita (1955) we introduce the concept of affinity between two complex distribution functions. We also establish a concrete expression for the affinity between two complex k-variate normal distributions when the covariance matrices assume a special form. Generalizations of these results are presented and the expressions here obtained are compared with those obtained by Matusita (1966, 1967) relative to the affinity between real k-variate normal...
Francisco Javier Girón, Carmen del Castillo (2001)
RACSAM
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La distribución de Behrens-Fisher generalizada se define como convolución de dos distribuciones t de Student y se relaciona con la distribución gamma invertida por medio de un teorema de representación como una mixtura, respecto del parámetro de escala, de distribuciones normales cuando la distribución de mezcla es la convolución de dos distribuciones gamma invertidas. Un resultado importante de este artículo establece que la distribución de Behrens-Fisher con grados de libertad impares...
Pedro Puig, Michael A. Stephens (2007)
SORT
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The skew-Laplace distribution is frequently used to fit the logarithm of particle sizes and it is also used in Economics, Engineering, Finance and Biology. We show the Anderson-Darling and Cramér-von Mises goodness of fit tests for this distribution.
José Tiago de Oliveira (1985)
Trabajos de Estadística e Investigación Operativa
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The purpose of this paper is to study the asymptotic choice between two models {F(x|α), α ∈ A ⊆ R} and {G(x|β), β ∈ B ⊆ R}, A and B being intervals but such that for (α, β}, and only for this pair, we have F(x|α) = G(x|β).