Technical Note: Trend estimation from irregularly sampled, correlated data
نویسندگان
چکیده
منابع مشابه
Time Series Analysis for Irregularly Sampled Data
Many spectral estimation methods for irregularly sampled data tend to be heavily biased at higher frequencies or fail to produce a spectrum that is positive for all frequencies. A time series spectral estimator is introduced that applies the principles of a new automatic equidistant missing data algorithm to unevenly spaced data. This time series estimator approximates the irregular data by a n...
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Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-specific temporal behaviors and this also in the case when the available patient-specific data are sp...
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Many methods have been developed for spectral analysis of irregularly sampled data. Current popular methods such as Lomb-Scargle and resampling tend to be biased at higher frequencies. Slotting methods fail to consistently produce a spectrum that is positive for all frequencies. In this paper, a new estimator is introduced that applies the Burg algorithm for AR spectral estimation to unevenly s...
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ژورنال
عنوان ژورنال: Atmospheric Chemistry and Physics
سال: 2010
ISSN: 1680-7324
DOI: 10.5194/acp-10-6737-2010