<p>In this article we present a method for simulating a multi-variate time series via a vector auto regressive moving average (p, q) process. We also carried out two simulation studies to check the performance of the method and applied the methodology to a real sea condition time series. All results show that the method works very well in practice.</p>
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
Vector Auto-regressive (VAR) models are commonly used for modelling multivariate time series and the...
We present a model for representing stationary multivariate time-series input processes with margina...
Thesis (M.S.)--Wichita State University, Fairmount College of Liberal Arts and Sciences, Dept. of Ma...
The autoregressive random variance (ARV) model proposed by Taylor (Financial returns modelled by the...
Time series analysis is used to predict future behaviour of processes and is widely used in the fina...
Joint time series of wave height, period and direction are essential input data to computational mod...
This dissertation consists of three chapters that contribute to different multivariate time series m...
Recent work has made the generation of univariate time series for inputs to stochastic systems quite...
In this paper we discuss stochastic models for vector processes, in particular the class of multivar...
Joint time series of wave height, period and direction are essential input data to computational mod...
In this paper a method for studying process dynamics will be presented. The method is based on stati...
In this paper a method for studying process dynamics will be presented. The method is based on stati...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
Vector Auto-regressive (VAR) models are commonly used for modelling multivariate time series and the...
We present a model for representing stationary multivariate time-series input processes with margina...
Thesis (M.S.)--Wichita State University, Fairmount College of Liberal Arts and Sciences, Dept. of Ma...
The autoregressive random variance (ARV) model proposed by Taylor (Financial returns modelled by the...
Time series analysis is used to predict future behaviour of processes and is widely used in the fina...
Joint time series of wave height, period and direction are essential input data to computational mod...
This dissertation consists of three chapters that contribute to different multivariate time series m...
Recent work has made the generation of univariate time series for inputs to stochastic systems quite...
In this paper we discuss stochastic models for vector processes, in particular the class of multivar...
Joint time series of wave height, period and direction are essential input data to computational mod...
In this paper a method for studying process dynamics will be presented. The method is based on stati...
In this paper a method for studying process dynamics will be presented. The method is based on stati...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
This article proposes an algorithm to generate vector moving average (VMA) processes with a variable...
Vector Auto-regressive (VAR) models are commonly used for modelling multivariate time series and the...
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