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    Sinusoidal model - Wikipedia

    In statistics, signal processing, and time series analysis, a sinusoidal model is used to approximate a sequence Yi to a sine function: $${\displaystyle Y_{i}=C+\alpha \sin(\omega T_{i}+\phi )+E_{i}}$$where C is constant defining a mean level, α is an amplitude for the sine, ω is the angular frequency, Ti is a time … See more

    Good starting value for the mean
    A good starting value for C can be obtained by calculating the mean of the data. If the data show a trend, i.e., the assumption of constant location is violated, one can replace C … See more

    As with any statistical model, the fit should be subjected to graphical and quantitative techniques of model validation. For example, a run sequence plot to check for significant shifts in … See more

    A different method consists in transforming the non-linear regression to a linear regression thanks to a convenient integral equation. Then, there is no need for initial guess and no need … See more

     
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  3. 2.3: Applications and Modeling with Sinusoidal Functions

    How do we model periodic data accurately with a sinusoidal function? What is a mathematical model? Why is it reasonable to use a sinusoidal function to …

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      Aug 12, 2024 · Learn how to build and interpret sinusoidal models from applications and data using the sine function. Understand the definitions and meanings of amplitude, period, phase shift, and frequency of sinusoidal waves.

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      A sine wave, sinusoidal wave, or sinusoid (symbol: ∿) is a periodic wave whose waveform (shape) is the trigonometric sine function. In mechanics, as a linear motion over time, this is simple harmonic motion; as rotation, it corresponds to …

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      Jul 16, 2024 · What can be modelled as a sinusoidal model? Anything that oscillates (fluctuates periodically) Examples include: D(t) is the depth of water at a shore t hours after midnight; T(d) is the temperature of a city d days after the …

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      Sinusoidal regression finds a trigonometric model that gives the curve of best fit. The idea is the same as finding the line of best fit in linear regression. However, instead of finding a straight line, this time you’ll find a sinusoidal curve.

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