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Twierdzenie Bayesa po 250 latach

100%
Szreder M.
Wiadomości Statystyczne. The Polish Statistician
|
2013
|
issue nr 12
23-26
XX
W artykule autor opisuje wpływ, jaki wywarło twierdzenie Bayesa nie tylko na rozwój teorii prawdopodobieństwa i wnioskowania statystycznego, ale też jako niezwykle użyteczne narzędzie w podejmowaniu decyzji w sytuacjach niepewności.
EN
The Author recalls that 250 years ago in the British scientific circles ap-peared theorem of probability of causes, now called Bayes' theorem (formulated in 1763 by Thomas Bayes). It refers to the situation where there has been some events and once need to assess the probability of another incident which was the reason, i.e. what is cause and what is the effect of this event. Despite the passing years Bayes' approach in statistical surveys for the conditional probability of occurrence is constantly confirmed and important. (original abstract)
2
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Chaotyczne reakcje rynków finansowych - aspekt probabilistyczny wyceny i zabezpieczeń płatniczych na rynku kapitałowym

84%
Szkutnik W.
Studia Ekonomiczne
|
2013
|
vol. 124
11-28
EN
Considered in developing the financial model of the exemplification of the market refers to the complete markets. Developed the idea not-self-financing the strategy at a fair valuation of the possible options. The appropriate development of this theme is the introduction to the issue of the financial model of incomplete markets and to structure the equity portfolio under the assumption of statistical indeterminacy. The derived formulas in the article is a basic introduction to the analysis of the financial market, but the aspect of perspective on this subject with seemingly very formalized, leading to appraise the relevant hedging approach equivalent security. The following article about the chaotic financial data responsive to capital markets. Examined aspect of distinguishing chaotic and stochastic defined in terms of looking at this problem. Discusses the correlation dimension as an assessment of the degree of chaos in time series data. Attention has been returned to the issue in various applications possible solutions to the tasks for the reconstruction of the evolution operator of futures markets. The basic premise is that any choice of non-linearities without introducing a priori information or special prior studies do not always object to select the successful reconstruction.
3
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Liniowa funkcja prawdopodobieństwa

84%
Wiśniewski J. W.
Studia Ekonomiczne
|
2017
|
vol. 324
161-172
PL
Ważnym narzędziem analitycznym w ekonometrii, służącym m.in. do badania asocjacji zmiennych zerojedynkowych, jest liniowa funkcja prawdopodobieństwa, zwana też modelem Goldbergera1. Jego specyfiką jest zerojedynkowa zmienna objaśniana, powodująca, że teoretyczne wartości modelu empirycznego są szacunkami prawdopodobieństwa wystąpienia wariantu sygnowanego liczbą 1. Zmienne objaśniające w modelu mogą być zarówno ciągłe, jak i dyskretne. Model Goldbergera jest ważnym instrumentem pomiaru uwarunkowań przyczynowych, głównie zmiennych jakościowych, ale również tzw. zmiennych ilościowych. Wymaga on jednak specyficznego podejścia, przede wszystkim do estymacji jego parametrów.
EN
An important analytical tool in econometrics, serving, inter alia, to investigate the association of dummy variables, is a linear function of probability. The function is also known as Goldberger model. Its specificity is the dummy dependent variable which causes, that theoretical values of the empirical model are empirical estimates of probability of a variant, signed as 1. The explanatory variables in the model can be both continuous or discrete. The Goldberger model is an important instrument for the measurement of the casual conditions, mainly qualitative variables, but also the quantitative variables. However, it requires a specific approach, primarily in estimating of its parameters.
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