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On formulae for central moments of counting distributions

Katarzyna Steliga, Dominik Szynal (2015)

Applicationes Mathematicae

The aim of this article is to give new formulae for central moments of the binomial, negative binomial, Poisson and logarithmic distributions. We show that they can also be derived from the known recurrence formulae for those moments. Central moments for distributions of the Panjer class are also studied. We expect our formulae to be useful in many applications.

On Fourier coefficient estimators consistent in the mean-square sense

Waldemar Popiński (1994)

Applicationes Mathematicae

The properties of two recursive estimators of the Fourier coefficients of a regression function f L 2 [ a , b ] with respect to a complete orthonormal system of bounded functions (ek) , k=1,2,..., are considered in the case of the observation model y i = f ( x i ) + η i , i=1,...,n , where η i are independent random variables with zero mean and finite variance, x i [ a , b ] R 1 , i=1,...,n, form a random sample from a distribution with density ϱ =1/(b-a) (uniform distribution) and are independent of the errors η i , i=1,...,n . Unbiasedness and mean-square...

On functional measures of skewness

Renata Dziubińska, Dominik Szynal (1996)

Applicationes Mathematicae

We introduce a concept of functional measures of skewness which can be used in a wider context than some classical measures of asymmetry. The Hotelling and Solomons theorem is generalized.

On generalized conditional cumulative past inaccuracy measure

Amit Ghosh, Chanchal Kundu (2018)

Applications of Mathematics

The notion of cumulative past inaccuracy (CPI) measure has recently been proposed in the literature as a generalization of cumulative past entropy (CPE) in univariate as well as bivariate setup. In this paper, we introduce the notion of CPI of order α and study the proposed measure for conditionally specified models of two components failed at different time instants, called generalized conditional CPI (GCCPI). Several properties, including the effect of monotone transformation and bounds of GCCPI...

On generalized information and divergence measures and their applications: a brief review.

Inder Jeet Taneja, Leandro Pardo, Domingo Morales, María Luisa Menéndez (1989)

Qüestiió

The aim of this review is to give different two-parametric generalizations of the following measures: directed divergence (Kullback and Leibler, 1951), Jensen difference divergence (Burbea and Rao 1982 a,b; Rao, 1982) and Jeffreys invariant divergence (Jeffreys, 1946). These generalizations are put in the unified expression and their properties are studied. The applications of generalized information and divergence measures to comparison of experiments and the connections with Fisher information...

On geometry of the set of admissible quadratic estimators of quadratic functions of normal parameters

Konrad Neumann, Stefan Zontek (2006)

Discussiones Mathematicae Probability and Statistics

We consider the problem of admissible quadratic estimation of a linear function of μ² and σ² in n dimensional normal model N(Kμ,σ²Iₙ) under quadratic risk function. After reducing this problem to admissible estimation of a linear function of two quadratic forms, the set of admissible estimators are characterized by giving formulae on the boundary of the set D ⊂ R² of components of the two quadratic forms constituting the set of admissible estimators. Different shapes and topological properties of...

On goodness-of-fit for the absence of memory model

Vilijandas Bagdonavičius, Rüta Levulienė (2001)

Kybernetika

Logrank-type and Kolmogorov-type goodness-of-fit tests for the absence of memory model are proposed when the accelerated experiments are done under step-stresses. The power of the test against the approaching alternatives is investigated. The theoretical results are illustrated with simulated data.

On identifiability of mixtures of independent distribution laws

Mikhail Kovtun, Igor Akushevich, Anatoliy Yashin (2014)

ESAIM: Probability and Statistics

We consider representations of a joint distribution law of a family of categorical random variables (i.e., a multivariate categorical variable) as a mixture of independent distribution laws (i.e. distribution laws according to which random variables are mutually independent). For infinite families of random variables, we describe a class of mixtures with identifiable mixing measure. This class is interesting from a practical point of view as well, as its structure clarifies principles of selecting...

On improving sensitivity of the Kalman filter

Petr Franěk (2002)

Kybernetika

The impact of additive outliers on a performance of the Kalman filter is discussed and less outlier-sensitive modification of the Kalman filter is proposed. The improved filter is then used to obtain an improved smoothing algorithm and an improved state-space model parameters estimation.

On inconsistency of Hellwig's variable choice method in regression models

Tadeusz Bednarski, Filip Borowicz (2009)

Discussiones Mathematicae Probability and Statistics

It is shown that a popular variable choice method of Hellwig, which is recommended in the Polish econometric textbooks does not enjoy a very basic consistency property. It means in particular that the method may lead to rejection of significant variables in econometric modeling. A simulation study and a real data analysis case are given to support theoretical results.

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