In the pursuit of portable, efficient and effective sleep staging systems, researchers have been testing a massive number of combinations of EEG features and classifiers. State of the art sleep classification ensembles achieve accuracy in the order of 90%. However, there is presently no consensus regarding the best set of features for identifying sleep stages with a single EEG channel, leading ...

This paper deals with a numerical scheme to approximate the mth moment of the solution of the one-dimensional random linear transport equation. The initial condition is assumed to be a random function and the transport velocity is a random variable. The scheme is based on local Riemann problem solutions and Godunov’s method. We show that the scheme is stable and consistent with an advective-dif...

Sequential Monte Carlo and quantum mechanical calculations of the electronic polarization of the ground and first vertical excited states of 1H-benzotriazole in water are made. Using statistically uncorrelated configurations and CASSCF ab initio calculations the increase in the ground and excited state dipole moments of 1Hbenzotriazole from gas phase to aqueous environment are obtained as 2.89 ...

This paper addresses the calculation of moments of complex Wishart and complex inverse Wishart distributed random matrices. Complex Wishart and complex inverse Wishart distributed random matrices are used in applications like radar, sonar, or seismics in order to model the statistical properties of complex sample covariance matrices and complex inverse sample covariance matrices, respectively. ...

To enable correct statistical inference, the knowledge about the existence of moments is crucial. The objective of this paper is to study the existence of the moments for the ratio Y X Z / = , where X and Y are arbitrary random variables with the additional assumption 0 ) 0 ( = = Y P . We present three existence theorems showing that specific behaviour of the distribution of Y in the neighbourh...

We introduce the Method of Simulated Moments (MSM) for estimating unknown parameters in dynamic models. The MSM is useful when there are empirical data related to the behavior of different entities and error terms do not follow any well-established distribution. Statistical moments such as mean and variance of empirical data can be matched against the moments of model-generated data in order to...

We consider random matrices, belonging to the groups U(n), O(n), SO(n), and Sp(n) and distributed according to the corresponding unit Haar measure. We prove that the moments of traces of powers of the matrices coincide with the moments of certain Gaussian random variables if the order of moments is low enough. Corresponding formulas, proved partly before by various methods, are obtained here in...

Recent research using statistical moments to describe moving shapes through an image sequence has led to an interest in reconstructing moving shapes from their moment description. This paper discusses how the moment description through a series of frames might be used to predict missing or intermediate frames within a sequence. Additionally, this highlights generic aspects of moment reconstruct...

Description The package implements the statistical theory of L-moments in R including L-moment estimation, probability-weighted moment estimation, parameter estimation for numerous familiar and not-so-familiar distributions, and L-moment estimation for the same distributions from the parameters. L-moments are derived from the expectations of order statistics and are linear with respect to the p...