stationary Gaussian random process
Joint modelling of repeated measurements and time-to-event outcomes: flexible model specification and exact likelihood inference.
... The random-effects or shared parameter approach to jointly modelling repeated measurement and event time data is conceptually attractive in many settings, but its routine application is hampered by computational ...
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Generation of Non Gaussian Wide Sense Stationary Random Processes with Desired PSDs and PDFs
... this process we need determining a nonlinear transform function to convert Gaussian distribution of to Rayleigh PDF, the PDFs of the amplitude and fre- quency can be calculated after the first approximation ...
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A comparative study of Gaussian geostatistical and Gaussian Markov random field models
... spatial Gaussian processes with a spatial covariance that is often just a function of distance and direction between ...a process is constant and the covariance function depends on the spatial vector ...
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Definition of Probability Characteristics of the Absolute Maximum of Non-Gaussian Random Processes by Example of Hoyt Process
... the process η ( ) t to be the Markov random ...the process η ( ) t can be ...the process η ( ) t (1) can be approximately considered by locally-Markov Hoyt process with the ...
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A test problem for molecular dynamics integrators
... We derive a test problem for evaluating the ability of time-stepping methods to preserve the statistical properties of systems in molecular dynamics. We consider a family of deterministic systems consisting of a finite ...
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Computationally Efficient Estimation of Non-stationary Gaussian Process Models for Large Spatial Data.
... overall stationary Gaussian ...generating random base ...a stationary model through 5-fold cross validation and found the non-stationary model superior in high resolution ...
100
A generalization of almost sure local limit theorem of uniform empirical process
... For Gaussian sequences, Csáki and Gonchigdanzan [] presented the validity of ...of stationary Gaussian sequences under some mild ...non-stationary Gaussian sequences. As for some other ...
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Numerical Approximation of Fractal Dimension of Gaussian Stochastic Processes
... ergodic stationary Gaussian stochastic processes associated with the random Ornstein Uhlenbeck ...Using random Euler scheme performed numerical construction of the expectation value, variance ...
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Kriging and Simulation in Gaussian Random Fields Applied to Soil Property Interpolation
... realization Gaussian random field ...isotropic stationary Gaussian process, that is achieved after ...in Gaussian random ...
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On the generation of inelastic secondary system seismic response spectra
... Considering the seismic movement as a Gaussian stationary random process, the proposed method by Almeida (2003), is used for generation of uniformly probable response spect[r] ...
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Extremes of a(t)-locally stationary Gaussian random fields
... α(t)-locally stationary Gaussian ...α(t)-locally stationary Gaussian process are derived, which can be applied, for instance, in the analysis of the extremes of standardized ...of ...
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Online Full Text
... the random vibrations generated by road transport ...current random vibration synthesis methods used for evaluating and validating the performance of packaging ...non-stationary random ...
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Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior
... As stated previously, the condition α > d/2 is necessary to obtain the optimal rate. van der Vaart and van Zanten (2009) showed that the squared-exponential covariance kernel without rescaling leads to a very slow ...
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Convergence of Multilevel Stationary Gaussian Quasi Interpolation
... The paper is organized as follows. In Section 2 we provide a precise statement of the problem we want to solve together with a description of the proposed multilevel solution method with Gaussian ...
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Choi_unc_0153D_12105.pdf
... of random effects is not a Gaussian distribution, the use of mixture is effective in longitudinal model but the inference on hazards model is reasonable regardless of ...
240
Study of the Convergence of the Increments of Gaussian Process
... Some Results for Partial Sums of Stationary Gaussian Sequence In this section we obtain similar results as Theorems 1 and 2 for the case of partial sums of a stationary Gaussian sequence[r] ...
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Non Stationary Random Process for Large Scale Failure and Recovery of Power Distribution
... We first formulate, from bottom up, an entire life cycle of large-scale failure and recovery. The problem for- mulation begins at the finest level of network nodes based on temporal-spatial stochastic processes. Since ...
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Joint time-frequency representation of simulated earthquake accelerograms via the adaptive chirplet transform
... The stationary part y(t) of the non-stationary process of Equation 15 is defined by an appropri- ately filtered Kanai-Tajimi power ...of stationary seismic waves, with unbiased frequency ...
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A Gaussian Process Approach for Extended Object Tracking with Random Shapes and for Dealing with Intractable Likelihoods
... In [12], a Rao-Blackwellised particle filter (RBPF) based approach is used to sample the kinematics states of object and a GP regression based Kalman filter is used to track extent. This approach provides improved ...
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Simulation of Seismic Waves
... However, most existing engineering simulations are based on Fourier analyses, which is for stationary random processes, while seismic waves are non-stationary random [r] ...
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