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Content available remote The Quantile Estimation of the Maxima of Sea Levels
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The hydrological modeling has become an intensively studied subject in recent years. One of the most significant problems concerning this issue is to provide the mathematical and statistical tools, which allow to forecast extreme hydrological events, such as severe sea or river floodings. The extreme events on water have huge social and economic impact on the affected areas. Due to these reasons, each country has to protect itself against the flood danger, and consequently, the designing of reliable flood defences is of great importance to the safety of the region. For example, the sea dikes along the Dutch coastline are designed to withstand floods, which may occur once every 10 000 years. It means that the height of the dike is determined in such a way that the probability of the event that there is a flood in a given year equals 10-4. The computation of such the height level requires the estimation of the corresponding quantiles of the distributions of certain maxima of sea levels. In our paper, we present the procedures, which lead to the estimation of such the quantiles. We are mainly concerned with the interval estimation; in this context, we present the frequentistic and Bayesian approaches in constructing the desired confidence intervals. (original abstract)
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Content available remote Comparison of Confidence Intervals for Fraction in Finite Populations
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Consider a finite population. Let θ ∈ (0,1) denotes the fraction of units with a given property. The problem is in interval estimation of θ on the basis of a sample drawn due to the simple random sampling without replacement. In the paper three confidence intervals are compared: exact based on hypergeometric distribution and two other based on approximations to hypergeometric distribution: Binomial and Normal. It appeared that Binomial based confidence interval is too conservative while the Normal based one does not keep the prescribed confidence level. (original abstract)
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Content available remote Robustness of the Confidence Interval for at-Risk-of-Poverty Rate
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Zieliński (2009) constructed a nonparametric interval for At-Risk-of-Poverty Rate. It appeared that the confidence level of the interval depends on the underlying distribution of the income. For some distributions (e.g. lognormal, gamma, Pareto) the confidence level may be smaller than the nominal one. The question is, what is the largest deviance from the nominal level? In the paper, a more general problem is considered, i.e. the problem of robustness of the confidence level of the confidence interval for binomial probability. The worst distribution is derived as well as the smallest true confidence level is calculated. Some asymptotic remarks (sample size tends to infinity) are also given. (original abstract)
Multi-criteria decision aid methods consider decision problems in which many alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results, since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE II-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE II method. On the basis of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE II's net flows, and then calculates weights. Subsequently, it aggregates the distribution masses associated with each criterion using Murphy's modified combination rule in order to infer a global belief structure. The final alternative ranking is obtained via pignistic probability transformation. A case study of a real-world application concerning the location of a treatment center of waste from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the PROMETHEE II-BELIEF approach. (original abstract)
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Content available remote Confidence Intervals for Fraction in Finite Populations : Minimal Sample Size
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Consider a finite population of N units. Let θ ∈ (0,1) denotes the fraction of units with a given property. The problem is in interval estimation of θ on the basis of a sample drawn due to the simple random sampling without replacement. It is of interest to obtain confidence intervals of a prescribed length. In the paper the minimal sample size which guarantees the length to not exceed the given value is calculated. (original abstract)
Jednym z problemów w badaniach ekonomiczno-społecznych jest oszacowanie odsetka odpowiedzi na pytania drażliwe. Pytania drażliwe są takimi pytaniami odpowiedzi na które respondent może nie udzielić rzetelnej odpowiedzi. W pracy podano konstrukcję dokładnego przedziału ufności dla tego odsetka i porównano zaproponowany przedział z przedziałami asymptotycznymi.(abstrakt oryginalny)
W pracy proponuje się subiektywne spojrzenie na teorię możliwości, polegające na założeniu, że kiedy konstruuje się pewien rozkład prawdopodobieństwa, jest on faktycznie indukowany przez pewną funkcję ufności (belief function) reprezentującą rzeczywisty stan wiedzy. Zakłada się również, że przejście od pewnej funkcji ufności do rozkładu prawdopodobieństwa jest realizowane za pomocą transformacji (pignistic transformation), znanej jako wartość Shapleya. Rozważa się problem znalezienia odpowiedniej funkcji ufności zgodnej z danym rozkładem prawdopodobieństwa. Dowodzi się, że funkcja ta jest jednoznacznie określona i zgodna. Można ją zatem reprezentować za pomocą rozkładu możliwości. Rozkład ten jest subiektywny i jednoznaczny. Otrzymane w pracy wyniki pozwalają na definiowanie subiektywnych stopni możliwości, a co za tym idzie - funkcji przynależności liczby rozmytej.
Most of the so far proposed Bonus-Malus Systems (BMSs) establish a premium only according to the number of accidents, without paying attention to the vehicle damage severity. [Frangos and Vrontos 2001] proposed the optimal BMS design based not only on the number of accidents of a policyholder, but also on the size of loss of each accident. In our work, we apply the approach presented by Frangos and Vrontos to construct the Bayesian confidence intervals for both the number of accidents and the amount of damage caused by these accidents. We also conduct some simulations in order to create tables of estimates for both the numbers and the sizes of losses and to compute the realizations of the corresponding Bayesian confidence intervals. We compare the results obtained by using our simulation studies with the appropriate results derived through an application of an asymmetric loss function and its certain modification. (original abstract)
Dokonano przeglądu literatury statystycznej dotyczącej przedziałów ufności dla kwantyli oraz współczynników ufności szacowanych z prób losowych otrzymanych przy różnych schematach jej losowania. Przegląd ten obejmuje najbardziej charakterystyczne prace w chronologii czasowej dotyczące wykorzystania kwantyli w metodzie reprezentacyjnej.
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