This function provides an estimate of probability density function for a given random data (an 1-d vector). The estimation can be done with a specified number of intervals, and bandwidth. Without any output, the function will plot the probability density function. A few examples are included to show how to use the function and its output.
It also includes bounded support. For some problems, bounded support is important. For example, many physical problems require positive variables. This function is able to estimate PDF for such problems as well if the lower and upper bounds are specified.
The new version includes cdf and inverse cdf estimation.
Excellent -- exactly what I needed.
The file has been upgraded to use Gaussian kernel smoothing estimation algorithm.
It's an ad hoc smoother:
One can search FEX for 'kernel density estimator'.
I havent tried this code, but it sounds very similar to matlabs ksdensity
Bug fix and new functionality
a bug fixed
update with cdf and inverse cdf estimation.
update with the optimal bandwidth
upgrade to use Gaussian kernel density estimation