What is Interpolation? Discuss the different
kinds of methods to solve interpolation
problems.
Answers
Answer:
Interpolation is a statistical method by which related known values are used to estimate an unknown price or potential yield of a security. Interpolation is achieved by using other established values that are located in sequence with the unknown value. Interpolation is at root a simple mathematical concept.
Answer:
Interpolation is a method of fitting the data points to represent the value of a function. It has a various number of applications in engineering and science, that are used to construct new data points within the range of a discrete data set of known data points or can be used for determining a formula of the function that will pass from the given set of points (x,y). In this article, we are going to discuss the meaning of interpolation in Statistics, its formulas, and uses in detail.
Step-by-step explanation:
Interpolation Methods
There are different types of interpolation methods. They are:
Linear Interpolation Method – This method applies a distinct linear polynomial between each pair of data points for curves, or within the sets of three points for surfaces.
Nearest Neighbour Method – This method inserts the value of an interpolated point to the value of the most adjacent data point. Therefore, this method does not produce any new data points.
Cubic Spline Interpolation Method – This method fits a different cubic polynomial between each pair of data points for curves, or between sets of three points for surfaces.
Shape-Preservation Method – This method is also known as Piecewise cubic Hermite interpolation (PCHIP). It preserves the monotonicity and the shape of the data. It is for curves only.
Thin-plate Spline Method – This method consists of smooth surfaces that also extrapolate well. It is only for surfaces only
Biharmonic Interpolation Method – This method is applied to the surfaces only.