density functions
Reconstruction of one-dimensional chaotic maps from sequences of probability density functions
... initial density function of the sorted cell frac- tion, by sampling and re-plating cells, over a number of ...of density functions generated in this process can then be used to infer the under- lying ...
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Higher Order Moments, Spectral and Bispectral Density Functions for INAR(1)
... This paper is organized as follows. In Section 2, some higher order joint moments of the NSINAR(1) model up to order three, the spec- tral and bispectral and normalized bispectral density functions are ...
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Calibration of numerical model output using nonparametric spatial density functions
... quantile functions for both models and data, and we apply a nonlinear monotonic regression approach on the quantile functions taking into account the spatial dependence to compare the density ...
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Cloud discrimination in probability density functions of limb-scattered sunlight measurements
... Probability density functions of scattering residuals show the distribution is not a continuum measurement; there is a distinction between the cloudy and cloud-free ...
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Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams
... approximating density functions of finite random persistence dia- grams has been ...kernel density function, as well as proof that the kernel density itself and its mean absolute deviation ...
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A refined statistical cloud closure using double-Gaussian probability density functions
... Compared to relative humidity schemes, PDF-based schemes typically need more and higher moments as in- put parameters. While the first two moments are commonly available in numerical weather prediction (NWP) models and ...
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LPM Density Functions for the Computation of the SD Efficient Set
... The close relationship between lower partial moments and stochastic dominance has been known since Porter [10], Bawa [1], Fishburn [2], and Bey [5]. This paper uses the known cumulative density function properties ...
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Calibration of Numerical Model Output using Nonparametric Spatial Density Functions.
... quantile functions for the observed temperature at the three cities, as well as the quantile func- tions estimated with the uncalibrated NARCCAP model outputs and the calibrated outputs using our Bayesian ...
86
Nonparametric estimating equations for circular probability density functions and their derivatives
... circular density estimation (and its derivatives) where local versions of population trigonometric moments are equated with their empirical ...unknown density by a periodic series expansion whose coefficients ...
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9 Form Follows Function: Reformulating Population Density Functions
... On both the theoretical and empirical sides of this argument, we also need to explore the link between entropy, information and dimension (Takayasu, 1989); for in doing so, we are likely[r] ...
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The distribution of productivity in Irish manufacturing between 1995 and 2004 : determinants, changes and implications
... probability density functions using a Gaussian kernel in 1995 and ...relative density function (RDF) that is obtained by setting the cumulative density functions of the 1995 and 2004 ...
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A Study on the Impact of Ethical Behaviour of Firms on Global Competitiveness Ranking
... of density functions by using contour transformations that depends on a slant ...unimodel density function with modal value zero. We obtain new density function f * by transforming the ...
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Age Related Changes in Probability Density Function of Pairwise Euclidean Distances between Multichannel Human EEG Signals
... probability density functions (pdf’s) of the EEG relative displacements ΔY τ (the Euc- lidean distances between scaled multichannel human EEG signals pairs at given time lag τ ) along this trajectory, ...
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Fluctuations of finite-time Lyapunov exponents in an intermediate-complexity atmospheric model: a multivariate and large-deviation perspective
... rate functions are estimated from time series of finite-time Lyapunov exponents based on the prob- ability density functions and using the Legendre transform ...rate functions at the minimum ...
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The Bayesian approach to statistics : a review of methodology with selected applications : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Statistics at Massey University
... Bayes Theorem in terms of probability density functions.. variable X, and its probability density function depends on the value of.[r] ...
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Efficient Density Estimation and Value at Risk Using Fejér Type Kernel Functions
... kernel functions are the most commonly applied in practice, most likely due to their additional nonnegative property as their corresponding estimators result in density ...kernel functions alternate ...
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Adaptive beamforming for binary phase shift keying communication systems
... Conditional probability density functions pðyj þ 1Þ surfaces, marginal conditional probability density functions pðyR j þ 1Þ curves, signal subsets YðþÞ and YðþÞ R points for the four-el[r] ...
11
Emulators for stochastic simulation codes
... integral equal to 1 and their negative values are interpreted as 0, hence the predictions on the experimental design are probability density functions. In the following two subsections we propose two new ...
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Transmutation Of The Two Parameters-Rayleigh Distribution On The Effect Of Physical Training On Age-Related Reduction Of GH Secretion During Exercise In Normally Cycling Women
... probability density function of the transmutation two parameters Rayleigh ...Probability density functions ( ) of transmutation of the two parameters Rayleigh distribution analysis on for the Effect ...
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B0 s lifetime measurement in the CP odd decay channel B0 s → J=ψ f 0 (980)
... proper decay length, and its uncertainty, respectively, for a given event j . The use of the probability density functions T and E follows the method of Ref. [15]. The specific models and parameters used in ...
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