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mathematical interpolation

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mathematical interpolation

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Also known as interpolation, numerical interpolation

In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing (finding) new data points based on the range of a discrete set of known data points.

AI overview

Interpolation is a mathematical technique for filling in missing values between known data points — imagine you have measurements at certain times or locations, and you want to estimate what the values would be at points in between. It matters because it allows scientists, engineers, and analysts to make educated guesses about unmeasured data and create smooth curves or surfaces from scattered information.

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~16 min read

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18 sections
Contents
  • Example
  • Piecewise constant interpolation
  • Linear interpolation
  • Polynomial interpolation
  • Spline interpolation
  • Mimetic interpolation
  • Functional interpolation
  • Function approximation
  • Via Gaussian processes
  • Inverse Distance Weighting
  • Other forms
  • In higher dimensions
  • In digital signal processing
  • Related concepts
  • Generalization
  • See also
  • References
  • External links

In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing (finding) new data points based on the range of a discrete set of known data points.

In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent variable. It is often required to interpolate; that is, estimate the value of that function for an intermediate value of the independent variable.

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