A Priori Information and Time Series Analysis. Essays in Economic Theory and Measurement

1963 ◽  
Vol 14 (2) ◽  
pp. 305
Author(s):  
Henri Guitton ◽  
F. M. Fisher ◽  
C. Kaysen
Keyword(s):  
Economic Theory ◽  
Time Series ◽  
Time Series Analysis ◽  
A Priori ◽  
A Priori Information ◽  
Series Analysis ◽  
Priori Information

A Priori Information and Time Series Analysis: Essays in Economic Theory and Measurement.

1964 ◽  
Vol 59 (306) ◽  
pp. 607
Author(s):  
Harry V. Roberts ◽  
Franklin M. Fisher
Keyword(s):  
Economic Theory ◽  
Time Series ◽  
Time Series Analysis ◽  
A Priori ◽  
A Priori Information ◽  
Series Analysis ◽  
Priori Information

A Priori Information and Time Series Analysis: A Review Article

1964 ◽  
Vol 5 (2) ◽  
pp. 228
Author(s):  
Susumu Koizumi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
A Priori ◽  
Review Article ◽  
A Priori Information ◽  
Series Analysis ◽  
Priori Information

scholarly journals An Algorithm for Estimating Fixed Points of Dynamical Systems from Time Series

1998 ◽  
Vol 08 (11) ◽  
pp. 2203-2213 ◽  
Author(s):  
Luis A. Aguirre ◽  
Álvaro V. P. Souza
Keyword(s):  
Time Series ◽  
Fixed Point ◽  
Dynamical Systems ◽  
Fixed Points ◽  
Prior Knowledge ◽  
A Priori ◽  
Real Data ◽  
A Priori Information ◽  
Chua's Circuit ◽  
Priori Information

This paper presents an algorithm for estimating fixed points of dynamical systems from time series. In some cases the new procedure can accurately estimate fixed points of which there is very little information in the data. Another advantage is that, although no prior knowledge is assumed, the new algorithm permits the user to employ a priori information about the system such as symmetry and the existence of a trivial fixed point. The new algorithm is tested on the Lorenz and Rössler systems and on real data taken from Chua's circuit.

scholarly journals Change-Point Detection using the Conditional Entropy of Ordinal Patterns

2018 ◽  
Author(s):  
Karsten Keller ◽  
Anton M. Unakafov
Keyword(s):  
Time Series ◽  
Change Point ◽  
Numerical Experiments ◽  
A Priori ◽  
Conditional Entropy ◽  
Change Point Detection ◽  
A Priori Information ◽  
Ordinal Patterns ◽  
Priori Information ◽  
Point Detection

This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated. The statistic requires only minimal a priori information on given data and shows good performance in numerical experiments.

scholarly journals Change-Point Detection Using the Conditional Entropy of Ordinal Patterns

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 709 ◽  
Author(s):  
Anton Unakafov ◽  
Karsten Keller
Keyword(s):  
Time Series ◽  
Change Point ◽  
Numerical Experiments ◽  
A Priori ◽  
Conditional Entropy ◽  
Change Point Detection ◽  
A Priori Information ◽  
Ordinal Patterns ◽  
Priori Information ◽  
Point Detection

This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated. The statistic requires only minimal a priori information on given data and shows good performance in numerical experiments. By the nature of ordinal patterns, the proposed method does not detect pure level changes but changes in the intrinsic pattern structure of a time series and so it could be interesting in combination with other methods.

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