Probability Density Functions For Selected Portfolio Sizes
Nonparametric forecasting of multivariate probability density functions
... 1 Introduction One of the most relevant research fields in theoretical and applied statistics is devoted to the study of the dependence between random variables. In finance, the analysis of the dependence patterns is a ...
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Physical interpretation of probability density functions of bubble-induced agitation
... The model involves parameters that need to be chosen. The gas volume fraction α, which is involved in all contributions, is a known parameter. The potential contribution depends on the bubble aspect ratio ξ, which is ...
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Nonparametric estimating equations for circular probability density functions and their derivatives
... A promising estimator has been included as a competitor, other than stan- dard kernel density method (p = 0). It is the circular local likelihood method described in [3]. Such an estimator can be defined as a ...
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Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams
... Here we present two more examples of constructing a kernel density estimator (KDE) according to the kernel given in Eq. (4.6). In these examples, we view slices of the KDE at various sample sizes and ...
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Joint probability density functions of random trajectories through a box
... Definitions dictating Case I allow for distinct behavior as a function of Box dimension as well as in comparison to Case II. This is in part due to the uniform distribution of trajectory angles, as illustrated in Figure ...
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A refined statistical cloud closure using double-Gaussian probability density functions
... subdomain sizes larger than 10 km the RMSE is small, being around ...subdomain sizes larger than 10 km, the cloud frac- tion as well as the liquid water are mostly overestimated by the double-Gaussian ...
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Optimal Portfolio Selection with a Shortfall Probability Constraint: Evidence from Alternative Distribution Functions
... optimal portfolio selection in a downside risk framework that allocates assets by maximizing expected return of a portfolio subject to a constraint on shortfall ...loss-averse portfolio with normal ...
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EMD-Based Filtering Using Similarity Measure Between Probability Density Functions of IMFs
... IV. C ONCLUSION In this paper, a new adaptive filtering strategy is presented. The filtering makes use of partial reconstruction, the relevant modes being selected on the basis of probabilistic similarity measure ...
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Audio Query by Example Using Similarity Measures between Probability Density Functions of Features
... were selected randomly, but the samples were screened by listening, and the samples having a significant amount of content from other categories than their class were ...
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OPTIMAL PORTFOLIO SELECTION WITH A SHORTFALL PROBABILITY CONSTRAINT: EVIDENCE FROM ALTERNATIVE DISTRIBUTION FUNCTIONS. Abstract
... Individual Stocks as Test Assets In this section, we partly repeat our analyses for a sample of individual stocks. The selected stocks are not chosen randomly but rather among those with a moderate to large ...
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Profile Monitoring of Probability Density Functions via Simplicial Functional PCA with application to Image Data
... a density increase of larger ...were selected because they provide realistic pore structures and challenging out-of-control deviations that may be difficult to detect with traditional monitoring ...
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Improving AoA Localization Accuracy in Wireless Acoustic Sensor Networks with Angular Probability Density Functions.
... 3.1. WASN-Node The node only wakes on an acoustic event, therefore a dedicated Acoustic Activity Detector (AAD) is present in the system. The AAD is always powered and activates the necessary components when sound is ...
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ESTIMATING AND INTERPRETING PROBABILITY DENSITY FUNCTIONS
... From a research point of view, however, it is impossible to disentangle the contribution of statistical probability and the contribution of relative marginal utility of different states. In the absence of a ...
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Kernel Density Smoothing Using Probability Density Functions and Orthogonal Polynomials
... kernel density smoothing, our approach revolves around introducing and testing the goodness of fit of some non-classical kernels based on probability density functions and orthogonal ...
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Gaussian Probability Density Functions: Properties and Error Characterization
... This problem can be stated the other way around. In the case where we specify a fixed probability value, the question is the value of K that yields an ellipsoid satisfying that probability. To answer the ...
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Probability density functions of some skew tent maps
... density function (pdf), for any of these maps. It is well known (Boyarsky A, Gora P. Laws of chaos: invariant measures and dynamical systems in one dimension. Boston: Birkhauser, 1997), that when a sequence of ...
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Estimation and regularization of probability density functions in image processing
... use probability theory, we specify on some topics, so let us focus on more concrete examples which are also important for the ...underlying probability density distribution which is added to an image ...
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Chapter 4 - Lecture 1 Probability Density Functions and Cumul. Distribution Functions
... I If in a Friday quiz we denote with X the time that the first student will finish and X follows a uniform distribution in the interval 5 to 15 minutes. I Find the cumulative distributio[r] ...
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Cloud discrimination in probability density functions of limb-scattered sunlight measurements
... Figure 1b shows a positive enhancement between 13.7 and 16.1 km tangent altitudes, suggesting the presence of clouds. Scattering residual profiles were generated and used to create histograms of scattering residuals. In ...
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Multiscale Characterization of the Probability Density Functions of Velocity and Temperature Increment Fields.
... the probability of exceedance as a measuring stick, it became clear that the differences between each location and height were minor, but some deviations existed especially near the tails at ±10 standard ...
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