probability density function

A probability density function is shown in the first figure below.

When the probability density function has its mode at 0.

Using a similar analysis, the probability density function of the product defect rate can be found.

A more accurate discussion of the probability density function can be found at Normal distribution.

Since is a probability density function for position, we calculate its standard deviation.

Now, represents the spatial probability density function of these random events in the following sense.

To see this, consider the joint probability density function of .

There are a couple of methods to generate a random number based on a probability density function.

This will construct a smooth probability density function from the supplied data.

A classical state of light is one in which is a probability density function.

An alternative but equivalent form of the probability density function is used in chromatography.

Let be a random variable with probability density function .

Take a draw from the probability density function that you specified for the 'taste' coefficients.

The probability density function of the Kent distribution is given by:

In the two variable case, the joint probability density function is given by:

Most stable distributions do not have a known closed form expression for their probability density functions.

Notice that M-estimators do not necessarily relate to a probability density function.

Which implies that the probability density function in that range is linear.

The degree of freedom used in the chi-squared probability density function is a positive number related to the target model.

For a normal distribution, the mode is the value that maximizes the probability density function.

The unconditional probability density function at a fixed time t:

The Wishart distribution can be characterized by its probability density function, as follows.

Probability density function of a ground state in a quantum harmonic oscillator.

A similar equation holds for the conditional probability density functions in the continuous case.

In most applications, for any , is a probability density function on .