Covariance Function - Parametric Families of Covariance Functions

Parametric Families of Covariance Functions

A simple stationary parametric covariance function is the "exponential covariance function"


C(d) = \exp(-d/V)

where V is a scaling parameter, and d=d(x,y) is the distance between two points. Sample paths of a Gaussian process with the exponential covariance function are not smooth. The "squared exponential covariance function"


C(d) = \exp(-d^2/V)

is a stationary covariance function with smooth sample paths.

The Matérn covariance function and rational quadratic covariance function are two parametric families of stationary covariance functions. The Matérn family includes the exponential and squared exponential covariance functions as special cases.

Read more about this topic:  Covariance Function

Famous quotes containing the words families and/or functions:

    There is a city myth that country life was isolated and lonely; the truth is that farmers and their families then had a richer social life than they have now. They enjoyed a society organic, satisfying and whole, not mixed and thinned with the life of town, city and nation as it now is.
    Rose Wilder Lane (1886–1965)

    One of the most highly valued functions of used parents these days is to be the villains of their children’s lives, the people the child blames for any shortcomings or disappointments. But if your identity comes from your parents’ failings, then you remain forever a member of the child generation, stuck and unable to move on to an adulthood in which you identify yourself in terms of what you do, not what has been done to you.
    Frank Pittman (20th century)