Add to ORKGWe discuss in this paper the problem of determining whether two time series have been produced by the same mechanism. In particular, we examine models and tech-niques for determining whether two series could have come from stochastic processes with the same continuous and discrete spectral characteristics. Key words: Stationary process, autoregression, sinusoids, hypothesis testing
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
In order to develop a method capable of determining the time variant spectrum of time series, variou...
We discuss in this paper the problem of determining whether two time series have been produced by th...
Empirical thesis.Bibliography: pages 95-97.1. Introduction -- 2. Literature review -- 3. Nonparametr...
We review spectral analysis and its application in inference for stationary processes. As can be see...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
The time series, studied e.g. in economics, biology, astronomy, constitute samples of stochastic pro...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
AbstractThis paper is concerned with the estimation of the spectral measure of a stationary process....
In the present work we study di®erent methods for testing whether or not a change has occurred in th...
Introduction Chapter I. Time Series 1.1 Sample of a stochastic process 1.2 Stationarity and trend of...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
In order to develop a method capable of determining the time variant spectrum of time series, variou...
We discuss in this paper the problem of determining whether two time series have been produced by th...
Empirical thesis.Bibliography: pages 95-97.1. Introduction -- 2. Literature review -- 3. Nonparametr...
We review spectral analysis and its application in inference for stationary processes. As can be see...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
The time series, studied e.g. in economics, biology, astronomy, constitute samples of stochastic pro...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
This paper is devoted to application of the singular-spectrum analysis to sequential detection of ch...
AbstractThis paper is concerned with the estimation of the spectral measure of a stationary process....
In the present work we study di®erent methods for testing whether or not a change has occurred in th...
Introduction Chapter I. Time Series 1.1 Sample of a stochastic process 1.2 Stationarity and trend of...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
Time series modeling as the sum of an autoregressive (AR) process and sinusoids is proposed. When th...
In order to develop a method capable of determining the time variant spectrum of time series, variou...