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2011 | 7 (14) | 241-251

Article title

Notes on line dependent coefficient and multiaverage

Title variants

Languages of publication

EN

Abstracts

EN
In this paper we discuss new statistic tools which enable more precise economics data analysis. Firstly, we define line dependent coefficientas a cosine of the angle made of the cross of regression lines. This is the basis thanks to which we can define other nonlinear relation coefficients such as conic dependent coefficient. Just like the classic correlation coefficient, line dependent coefficient is also asymptotically normal. The second part of this article is about multiaverage, a generalization of the classic expected value of the random variable idea. The average may be considered as the root-mean-square average approximation of the random variable with one point. Multiaverage is an approximation of the random variable with more than just one point at the same time (which is important when we talk about random variables, whose distributions are mixtures, or about multimodal densities). While defining multiaverage, we use the standard moments method and some facts from the orthogonal polynomial theory. In this paper we give some numerical examples in which we use the aforementioned tools.

Year

Issue

Pages

241-251

Physical description

Contributors

References

  • Antoniewicz R. (1988). Metoda najmniejszych kwadratów dla zależności niejawnych i jej zastosowania w ekonomii. PN AE we Wrocławiu nr 445. Wrocław.
  • Antoniewicz R. (2005). O średnich i przeciętnych. Wydawnictwo AE we Wrocławiu. Wrocław.
  • Bateman H., Erdelyi A. (1953). Higher Transcendental Functions. McGraw-Hill Book Company. New York.
  • Brandt S. (1999). Data Analysis. Statistical and Computational Methods for Statistics and Engineers. 3rd editiom. Springer Verlag. New York.
  • Cramer H. (1958). Metody matematyczne w statystyce. PWN. Warszawa. McLachlan G., Peel D. (2004). Finite Mixture Models. John Wiley & Sons. New York.
  • Stanisz T. (1993). Funkcje jednej zmiennej w badaniach ekonomicznych. PWN. Warszawa.
  • Szego G. (1975). Orthogonal Polynomials. Coll. Publ., XXIII. Amer. Math. Soc. Providence.
  • Wilkowski A. (1995). The coefficient of dependence for consumption curve. Argumenta Oeconomica. No. 1.
  • Wilkowski A. (2009). Uwagi o współczynniku korelacji. Ekonometria. Vol. 27.
  • Wilkowski A. (2008). Notes on normal distribution. Didactics of Mathematics. No. 5.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-af92d80a-0b3b-4515-ae6a-3563919f21b3
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