This function can be found by differentiating the cumulative distribution function.
This function is estimated using window functions in Parzen's method. It is equal to one over two pi times the Fourier transform of the characteristic function. Performing a double-sided Laplace transform-like operation on this function, but without the negative sign in the exponential, yields the moment-generating function. For a random variable x, integrating x times this function of x over the sample space gives the expectation of x. The integral of this non-negative function over all possible inputs must equal one. This function can be found by differentiating the cumulative distribution function. For 10 points, name this function for a continuous distribution whose integral from a to b gives the probability that x lies between a and b, and thus can be thought of as giving the relative probability that a random variable has value x.
This function is estimated using window functions in Parzen's method.
probability density function [or pdf; prompt on probability function]