Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, signal processing, and time series analysis, a sinusoidal model to approximate a sequence Yi is: Yi = C + αsin(ωTi + φ) + Ei where C is constant defining a mean level, α is an amplitude for the sine wave, ω is the frequency, Ti is a time variable, φ is the phase, and Ei is the error sequence in approximating the sequence Yi by the model. This sinusoidal model can be fit using nonlinear least squares; to obtain a good fit, nonlinear least squares routines may require good starting values for the constant, the amplitude, and the frequency. Fitting a model with a single sinusoid is a special case of least-squares spectral analysis.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Quality Content by WIKIPEDIA articles! In statistics, signal processing, and time series analysis, a sinusoidal model to approximate a sequence Yi is: Yi = C + sin( Ti + ) + Ei where C is constant defining a mean level, is an amplitude for the sine wave, is the frequency, Ti is a time variable, is the phase, and Ei is the error sequence in approximating the sequence Yi by the model. This sinusoidal model can be fit using nonlinear least squares; to obtain a good fit, nonlinear least squares routines may require good starting values for the constant, the amplitude, and the frequency. Fitting a model with a single sinusoid is a special case of least-squares spectral analysis. 132 pp. Englisch. N° de réf. du vendeur 9786131191886
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In statistics, signal processing, and time series analysis, a sinusoidal model to approximate a sequence Yi is: Yi = C + sin( Ti + ) + Ei where C is constant defining a mean level, is an amplitude for the sine wave, is the frequency, Ti is a time variable, is the phase, and Ei is the error sequence in approximating the sequence Yi by the model. This sinusoidal model can be fit using nonlinear least squares; to obtain a good fit, nonlinear least squares routines may require good starting values for the constant, the amplitude, and the frequency. Fitting a model with a single sinusoid is a special case of least-squares spectral analysis. N° de réf. du vendeur 9786131191886
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Taschenbuch. Etat : Neu. Sinusoidal Model | Statistics, Signal Processing, Time Series Analysis, Sine Wave | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131191886 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 113281848
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In statisticssignal processing, and time series analysis, a sinusoidal model toapproximate a sequence Yi is: Yi = C + ¿sin(¿Ti + ¿) + Ei where C isconstant defining a mean level, ¿ is an amplitude for the sine wave, ¿is the frequency, Ti is a time variable, ¿ is the phase, and Ei is theerror sequence in approximating the sequence Yi by the model. Thissinusoidal model can be fit using nonlinear least squares; to obtain agood fit, nonlinear least squares routines may require good startingvalues for the constant, the amplitude, and the frequency. Fitting amodel with a single sinusoid is a special case of least-squares spectralanalysis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch. N° de réf. du vendeur 9786131191886
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