Sinusoidal Model
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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.…mehr

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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.