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Estimation of Stationary Densities for Markov Chains
Estimation Stationary Densities Markov Chains
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2015/7/8
We describe a new estimator of the stationary density of a Markov chain on general state space. The new estimator is easier to compute, converges faster, and empirically gives visually superior estima...
Bounding Stationary Expectations of Markov Processes
Markov processes diff usions stationary bounds Poisson’s equation queueing
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2015/7/6
This paper develops a simple and systematic approach for obtaining bounds on stationary expectations of Markov processes. Given a function f which one is interested in evaluating, the main idea is to ...
On the Convergence of Finite Order Approximations of Stationary Time Series
Wide sense stationary time series autoregressive estimate moving average estimate
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2015/7/6
The approximation of a stationary time-series by finite order autoregressive (AR) and moving averages (MA) is a problem that occurs in many applications. In this paper we study asymptotic behavior of ...
Analysis of a Stochastic Approximation Algorithm for Computing Quasi-stationary Distributions
Stochastic approximations quasi-stationary distribution ODE method.
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2015/7/6
This paper analyzes the convergence properties of an iterative Monte Carlo procedure proposed in the Physics literature for estimating the quasi-stationary distribution on a transient set of a Markov ...
Fourier analysis of stationary time series in function space
Cumulants discrete Fourier transform functional data analy-sis functional time series periodogram operator spectral density operator weak depen-dence
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2013/6/14
We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in su...
Statistical estimation of quadratic Rényi entropy for a stationary m-dependent sequence
Entropy estimation quadratic R′enyi entropy stationarym-dependent sequence inter-point distances U-statistics
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2013/4/27
The R\'enyi entropy is a generalization of the Shannon entropy and is widely used in mathematical statistics and applied sciences for quantifying the uncertainty in a probability distribution. We cons...
A Novel Exact Representation of Stationary Colored Gaussian Processes (Fractional Differential Approach)
Digital Filtering Filtered White Noises Power Spectral Density Fractional Brownian Motion Fractional Stochastic Differential Equation Fractional Spectral Moments
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2013/4/28
A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output ...
Second-Order Non-Stationary Online Learning for Regression
Second-Order Non-Stationary Online Learning for Regression
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2013/4/28
The goal of a learner, in standard online learning, is to have the cumulative loss not much larger compared with the best-performing function from some fixed class. Numerous algorithms were shown to h...
On non-stationary threshold autoregressive models
explosive TAR(1) model least-squares estimator unit root TAR(1) model
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2011/7/19
In this paper we study the limiting distributions of the least-squares estimators for the non-stationary first-order threshold autoregressive (TAR(1)) model. It is proved that the limiting behaviors o...
Efficient sampling of high-dimensional Gaussian fields: the non-stationary / non-sparse case
Efficient sampling high-dimensional Gaussian non-stationary non-sparse case
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2011/6/20
This paper is devoted to the problem of sampling Gaussian fields
in high dimension. Solutions exist for two specific structures of inverse
covariance : sparse and circulant. The proposed approach is...
Covariance Matrix Estimation for Stationary Time Series
Autocovariance matrix banding large deviation physical dependence mea-sure short range dependence spectral density stationary process tapering thresholding Toeplitz matrix
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2011/6/20
We obtain a sharp convergence rate for banded covariance matrix estimates of stationary
processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices.
We also ...
Strictly stationary solutions of multivariate ARMA equations with i.i.d. noise
Strictly stationary solutions multivariate ARMA equations i.i.d. noise
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2011/6/17
We obtain necessary and sufficient conditions for the existence of strictly stationary
solutions of multivariate ARMA equations with independent and identically
distributed noise. For general ARMA(p...
Asymptotic Inference of Autocovariances of Stationary Processes
Autocovariance blocks of blocks bootstrapping Box-Pierce test extreme value distribution moderate deviation normal comparison physical dependence measure short range dependence stationary process summability of cumulants
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2011/6/17
The paper presents a systematic theory for asymptotic inference of autocovariances of
stationary processes.We consider nonparametric tests for serial correlations based on the maximum (or
L1) and th...
Estimating and forecasting partially linear models with non stationary exogeneous variables
-mixing additive models backtting electricity consumption forecasting interval semipara-metric regression smoothing
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2011/3/24
This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise. A rate of conve...
Estimating and forecasting partially linear models with non stationary exogeneous variables
-mixing additive models backfitting electricity consumption forecasting interval semipara-metric regression smoothing
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2011/3/23
This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise. A rate of conve...