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< 16.6 Summary and Problems | Contents | 17.1 Interpolation Problem Statement >

Chapter 17. Interpolation


The previous chapter used regression to find the parameters of a function that best estimated a set of data points. Regression assumes that the data set has measurement errors, and that you need to find a set of model parameters that minimize the error between your model and the data. However, sometimes you have measurements that are assumed to be very reliable; in these cases, you want an estimation function that goes through the data points you have. This technique is commonly referred to as interpolation.

By the end of the chapter, you should be able to understand and compute some of those most common interpolating functions.