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Create your own 1. function in MATLAB to calculate the probability density function (PDF) and cumulative distribution function (CDF) of a random variable that is one of the input arguments. Your function should output the location of each ‘bin’ and the respective PDF value, p(x). Use the first few lines below as a guide for your methodology. When you have created this function, test its output against the ‘hist’ or ‘histogram’ MATLAB routines (scaled properly) on sample data you have either collected or created. Include a plotting routine inside of your function file for the input data using the ‘bar’ and ‘plot’ commands. Inside of your function, • You should not reassign the input variables. Don’t have a line that says ‘x = randn(1000,1);’ for example. That should be done outside of the function, like so [bins, PDF] = pdf(randn(1000,1), 40); • Do not use the ‘hist’ or ‘histogram’ routines to compute the PDF or CDF. They should only be used to check your algorithm • You should rely on basic logic functions such as if, else, for, while, etc. Where applicable, you may use min(), max(), length(), size(), find(), and diff() among other basic functions built-in to MATLAB such as plot(), title(), xlabel(), and so on.
1 function [binsx, px] = pdf_plot(x, Nx) 2 % PDF - calculates a probability density function 3 % x = input data vector ** Do NOT overwrite! ** 4 % Nx = desired # bins for x ** Do NOT overwrite! ** 5 % px = probability density function 6 % binsx = centers of bin locations for px
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