Data estimation and the colour of time series. 2001

I Scheuring, and O E Zeöld
Department of Plant Taxonomy and Ecology, Research Group of Ecology and Theoretical Biology, Eötvös University, Pdzmàny Péter Sétány 1/B, Budapest, H-1117, Hungary. shieazsf@ludens.elte.hu

There has been a long debate on the source of temporal fluctuations in natural population densities. The difficulty is that unpredictable irregularities might be attributed either to external environmental factors or to chaotic dynamics of populations, or even to the interaction of these two factors. Some years ago Cohen (1995) pointed out that real time series follow redshifted Fourier power spectra, while the simplest chaotic population dynamical models are mostly blueshifted. Since then, the controversy has focused on comparisons of Fourier spectra originating from different models and data. Here, we show experimentally that estimation process by human observers shifts power spectra to the red. This result implies that because of estimation distortion, real population data must be less redshifted than many recorded time series suggest.

UI MeSH Term Description Entries
D011157 Population Dynamics The pattern of any process, or the interrelationship of phenomena, which affects growth or change within a population. Malthusianism,Neomalthusianism,Demographic Aging,Demographic Transition,Optimum Population,Population Decrease,Population Pressure,Population Replacement,Population Theory,Residential Mobility,Rural-Urban Migration,Stable Population,Stationary Population,Aging, Demographic,Decrease, Population,Decreases, Population,Demographic Transitions,Dynamics, Population,Migration, Rural-Urban,Migrations, Rural-Urban,Mobilities, Residential,Mobility, Residential,Optimum Populations,Population Decreases,Population Pressures,Population Replacements,Population Theories,Population, Optimum,Population, Stable,Population, Stationary,Populations, Optimum,Populations, Stable,Populations, Stationary,Pressure, Population,Pressures, Population,Replacement, Population,Replacements, Population,Residential Mobilities,Rural Urban Migration,Rural-Urban Migrations,Stable Populations,Stationary Populations,Theories, Population,Theory, Population,Transition, Demographic,Transitions, Demographic
D005583 Fourier Analysis Analysis based on the mathematical function first formulated by Jean-Baptiste-Joseph Fourier in 1807. The function, known as the Fourier transform, describes the sinusoidal pattern of any fluctuating pattern in the physical world in terms of its amplitude and its phase. It has broad applications in biomedicine, e.g., analysis of the x-ray crystallography data pivotal in identifying the double helical nature of DNA and in analysis of other molecules, including viruses, and the modified back-projection algorithm universally used in computerized tomography imaging, etc. (From Segen, The Dictionary of Modern Medicine, 1992) Fourier Series,Fourier Transform,Analysis, Cyclic,Analysis, Fourier,Cyclic Analysis,Analyses, Cyclic,Cyclic Analyses,Series, Fourier,Transform, Fourier
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D012680 Sensitivity and Specificity Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed) Specificity,Sensitivity,Specificity and Sensitivity
D012815 Signal Processing, Computer-Assisted Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity. Digital Signal Processing,Signal Interpretation, Computer-Assisted,Signal Processing, Digital,Computer-Assisted Signal Interpretation,Computer-Assisted Signal Interpretations,Computer-Assisted Signal Processing,Interpretation, Computer-Assisted Signal,Interpretations, Computer-Assisted Signal,Signal Interpretation, Computer Assisted,Signal Interpretations, Computer-Assisted,Signal Processing, Computer Assisted
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016013 Likelihood Functions Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters. Likelihood Ratio Test,Maximum Likelihood Estimates,Estimate, Maximum Likelihood,Estimates, Maximum Likelihood,Function, Likelihood,Functions, Likelihood,Likelihood Function,Maximum Likelihood Estimate,Test, Likelihood Ratio

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