We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequency domain tests about the spectral density matrix of a multivariate time series. Under a set of easy to verify conditions, we establish asymptotic validity of the proposed bootstrap procedure. We apply a version of this procedure together with a new statistic in order to test the hypothesis tha...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

Background: The artificial neural networks (ANNs) are useful in solving nonlinear processes, without the need for mathematical models of the parameters. Since the relationship between the CT numbers and material compositions is not linear, ANN can be used for obtaining tissue density and composition.Objective: The aim of this study is to utilize ANN for determination of the composition and mass...

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

Virtual characters in games and simulations often need to plan visually convincing paths through a crowded environment. This paper describes how crowd density information can be used to guide a large number of characters through a crowded environment. Crowd density information helps characters avoid congested routes that could lead to traffic jams. It also encourages characters to use a wide va...

Central banks and other forecasters have become increasingly interested in various aspects of density forecasts. However, recent sharp changes in macroeconomic volatility — such as the Great Moderation and the more recent sharp rise in volatility associated with greater variation in energy prices and the deep global recession — pose significant challenges to density forecasting. Accordingly, th...

We show that the relaxational dynamics as exhibited in the enthalpy relaxation of the density wave compounds at very low temperatures (T<lK) is very similar to that one occuring in disordered systems such as glassy polymers or spin glasses. We discuss these similarities, as well as some pecularities, in the frame of secondary relaxational processes as genuine features of glass formers below the...