We are concerned here with the practical study of periodicities in phenomena which can be qualified as « historical », i. e. stochastic, non-reproducible, whose measurements extend over a limited time, and contain vacancies due to incidental conditions. Several methods are discussed here : periodogram, power spectrum, autocorrelation function, and a mixed method (autocorrelation multiplied by power spectrum) which yielded some good results.Nous nous intéressons ici à la détermination pratique de périodicités dans des phénomènes « historiques », c'est-à-dire aléatoires, non reproductibles, dont les mesures sont limitées dans le temps, et qui en outre comportent des manques dus à diverses causes fortuites. Nous présentons ici, avec critiques,...
Data of time series (or another nonrandom variables) show large fluctuations between successive valu...
"Autocorrelation and frequency analyses of a series of aperiodic time events, in particular, filtere...
We develop a general framework for the frequency analysis of irregularly sampled time series. It is ...
Nous nous intéressons ici à la détermination pratique de périodicités dans des phénomènes « historiq...
This work is concerned mainly with the earth's magnetism and its division in terms of time perturbat...
International audienceIn condition monitoring a part of the information necessary for decision-makin...
Two simple period determination schemes are discussed. They are well suited to problems involving no...
This thesis presents the partial autocorrelation function of a nonstationary process and some applic...
Abstract The classical power spectrum, computed in the frequency domain, outranks traditionally used...
<p>Note that there is an alternating pattern of peaks and troughs with a period of about 150 My, and...
Abstract The classical power spectrum, computed in the frequency domain, outranks traditionally used...
International audienceUn rapide tour d'horizon des publications récentes montre que les bornes chron...
We review spectral analysis and its application in inference for stationary processes. As can be see...
AbstractDiscovering and analysis of hidden periodicities are formulated as a problem of period and p...
National audienceThis paper proposes a stochastic modeling of time series of items to mine period...
Data of time series (or another nonrandom variables) show large fluctuations between successive valu...
"Autocorrelation and frequency analyses of a series of aperiodic time events, in particular, filtere...
We develop a general framework for the frequency analysis of irregularly sampled time series. It is ...
Nous nous intéressons ici à la détermination pratique de périodicités dans des phénomènes « historiq...
This work is concerned mainly with the earth's magnetism and its division in terms of time perturbat...
International audienceIn condition monitoring a part of the information necessary for decision-makin...
Two simple period determination schemes are discussed. They are well suited to problems involving no...
This thesis presents the partial autocorrelation function of a nonstationary process and some applic...
Abstract The classical power spectrum, computed in the frequency domain, outranks traditionally used...
<p>Note that there is an alternating pattern of peaks and troughs with a period of about 150 My, and...
Abstract The classical power spectrum, computed in the frequency domain, outranks traditionally used...
International audienceUn rapide tour d'horizon des publications récentes montre que les bornes chron...
We review spectral analysis and its application in inference for stationary processes. As can be see...
AbstractDiscovering and analysis of hidden periodicities are formulated as a problem of period and p...
National audienceThis paper proposes a stochastic modeling of time series of items to mine period...
Data of time series (or another nonrandom variables) show large fluctuations between successive valu...
"Autocorrelation and frequency analyses of a series of aperiodic time events, in particular, filtere...
We develop a general framework for the frequency analysis of irregularly sampled time series. It is ...