A Modular Approach for the Diagnostic Analysis of Dynamic Systems Using Stochastic Time-Series Models

1982 ◽  
Vol 12 (6) ◽  
pp. 794-804 ◽  
Author(s):  
Belle R. Upadhyaya ◽  
Malgorzata Skorska
Keyword(s):  
Time Series ◽  
Dynamic Systems ◽  
Time Series Models ◽  
Modular Approach ◽  
Diagnostic Analysis ◽  
Stochastic Time Series ◽  
Stochastic Time

scholarly journals A note on one-dimensional chaotic maps under time reversal

1992 ◽  
Vol 24 (1) ◽  
pp. 219-220 ◽  
Author(s):  
H. Tong ◽  
B. Cheng
Keyword(s):  
Time Series ◽  
Time Reversal ◽  
Chaotic Maps ◽  
Time Series Models ◽  
Deterministic Models ◽  
One Dimensional ◽  
Stochastic Time Series ◽  
Stochastic Time

We have furnished further examples on the connection between some standard one-dimensional chaotic deterministic models and stochastic time series models via time reversal.

Estimation of P(Z

1999 ◽  
Vol 104 (2-3) ◽  
pp. 179-189 ◽  
Author(s):  
Mostafa S. Aminzadeh
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Stochastic Time Series ◽  
Stochastic Time

Does Inflation Vary between Cities?

1984 ◽  
Vol 16 (4) ◽  
pp. 513-527 ◽  
Author(s):  
G L Clark
Keyword(s):  
Time Series ◽  
Urban Areas ◽  
Time Series Models ◽  
Theoretical Argument ◽  
Price Equilibrium ◽  
Price Inflation ◽  
Quarterly Data ◽  
Spatial Price ◽  
Stochastic Time Series ◽  
Stochastic Time

Apart from occasional anecdotal observation, there has been little systematic study of the patterns of local inflation. The strongest theoretical argument is that local price inflation should be no different from national inflation. Alternatively, it has been suggested that spatial price equilibrium is implausible and that spatial price interdependence is more likely. Quarterly data for some sixteen large US urban areas over the period 1950–1980, are analyzed via stochastic time-series models. It is concluded in this paper that, although inflation does vary, if only slightly, between cities and with respect to the nation, in some instances national inflation may fairly represent local inflation.

Error bounds for deterministic approximations to Markov processes, with applications to epidemic models

1995 ◽  
Vol 32 (04) ◽  
pp. 1063-1076 ◽  
Author(s):  
J. Gani ◽  
Sid Yakowitz
Keyword(s):  
Time Series ◽  
Numerical Analysis ◽  
Confidence Interval ◽  
Computational Study ◽  
Random Processes ◽  
Time Series Models ◽  
Practical Procedure ◽  
Hiv Epidemic ◽  
Stochastic Time Series ◽  
Stochastic Time

The computer age and the phenomenological complexity of the AIDS/HIV epidemic have engendered a rich profusion of deterministic and stochastic time series models for the development of an epidemic. The present study examines the reliability of deterministic approximations of fundamentally random processes. Through numerical analysis and probabilistic considerations, we derive absolute and simultaneous confidence interval bounding techniques, and offer a practical procedure based on these developments. A heartening aspect of the computational study presented at the close of this paper indicates that when the population size is in the thousands, the deterministic version to the classical logistic epidemic is a good approximation.

scholarly journals A note on one-dimensional chaotic maps under time reversal

1992 ◽  
Vol 24 (01) ◽  
pp. 219-220 ◽  
Author(s):  
H. Tong ◽  
B. Cheng
Keyword(s):  
Time Series ◽  
Time Reversal ◽  
Chaotic Maps ◽  
Time Series Models ◽  
Deterministic Models ◽  
One Dimensional ◽  
Stochastic Time Series ◽  
Stochastic Time

We have furnished further examples on the connection between some standard one-dimensional chaotic deterministic models and stochastic time series models via time reversal.

Error bounds for deterministic approximations to Markov processes, with applications to epidemic models

1995 ◽  
Vol 32 (4) ◽  
pp. 1063-1076 ◽  
Author(s):  
J. Gani ◽  
Sid Yakowitz
Keyword(s):  
Time Series ◽  
Numerical Analysis ◽  
Confidence Interval ◽  
Computational Study ◽  
Random Processes ◽  
Time Series Models ◽  
Practical Procedure ◽  
Hiv Epidemic ◽  
Stochastic Time Series ◽  
Stochastic Time

The computer age and the phenomenological complexity of the AIDS/HIV epidemic have engendered a rich profusion of deterministic and stochastic time series models for the development of an epidemic. The present study examines the reliability of deterministic approximations of fundamentally random processes. Through numerical analysis and probabilistic considerations, we derive absolute and simultaneous confidence interval bounding techniques, and offer a practical procedure based on these developments. A heartening aspect of the computational study presented at the close of this paper indicates that when the population size is in the thousands, the deterministic version to the classical logistic epidemic is a good approximation.

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