<< Chapter < Page Chapter >> Page >

mgsumn.m function [z,pz] = mgsumn(varargin) is an alternate to mgnsum, utilizing varargin in MATLAB version 5.1. The call is of the form [z,pz] = mgsumn([x1;p1],[x2;p2], ..., [xn;pn]) .

function [z,pz] = mgsumn(varargin)% MGSUMN [z,pz] = mgsumn([x1;p1],[x2;p2], ..., [xn;pn]) % Version of 6/2/97 Uses MATLAB version 5.1% Sum of n independent simple random variables % Utilizes distributions in the form [x;px](two rows) % Iterates mgsumn = length(varargin); % The number of distributions z = 0; % Initializationpz = 1; for i = 1:n % Repeated use of mgsum[z,pz] = mgsum(z,varargin{i}(1,:),pz,varargin{i}(2,:));end
Got questions? Get instant answers now!

diidsum.m function [x,px] = diidsum(X,PX,n) determines the sum of n iid simple random variables, with the common distribution X , P X .

function [x,px] = diidsum(X,PX,n)% DIIDSUM [x,px] = diidsum(X,PX,n) Sum of n iid simple random variables% Version of 10/14/95 Input rev 5/13/97 % Sum of n iid rv with common distribution X, PX% Uses m-function mgsum x = X; % Initializationpx = PX; for i = 1:n-1[x,px] = mgsum(x,X,px,PX);end
Got questions? Get instant answers now!

itest.m Tests for independence the matrix P of joint probabilities for a simple pair { X , Y } of random variables.

% ITEST file itest.m Tests P for independence % Version of 5/9/95% Tests for independence the matrix of joint % probabilities for a simple pair {X,Y}pt = input('Enter matrix of joint probabilities '); disp(' ')px = sum(pt); % Marginal probabilities for X py = sum(pt'); % Marginal probabilities for Y (reversed)[a,b] = meshgrid(px,py);PT = a.*b; % Joint independent probabilities D = abs(pt - PT)>1e-9; % Threshold set above roundoff if total(D)>0 disp('The pair {X,Y} is NOT independent')disp('To see where the product rule fails, call for D') elsedisp('The pair {X,Y} is independent') end
Got questions? Get instant answers now!

idbn.m function p = idbn(px,py) uses marginal probabilities to determine the joint probability matrix (arranged as on the plane) for an independent pair of simple randomvariables.

function p = idbn(px,py) % IDBN p = idbn(px,py) Matrix of joint independent probabilities% Version of 5/9/95 % Determines joint probability matrix for two independent% simple random variables (arranged as on the plane) [a,b]= meshgrid(px,fliplr(py)); p = a.*b
Got questions? Get instant answers now!

isimple.m Takes as inputs the marginal distributions for an independent pair { X , Y } of simple random variables. Sets up the joint distribution probability matrix P as in idbn , and forms the calculating matrices t , u as in jcalc . Calculates basic quantities and makes available matrices X , Y , P X , P Y , P , t , u for additional calculations.

% ISIMPLE file isimple.m Calculations for independent simple rv % Version of 5/3/95X = input('Enter row matrix of X-values '); Y = input('Enter row matrix of Y-values ');PX = input('Enter X probabilities '); PY = input('Enter Y probabilities ');[a,b] = meshgrid(PX,fliplr(PY));P = a.*b; % Matrix of joint independent probabilities [t,u]= meshgrid(X,fliplr(Y)); % t, u matrices for joint calculations EX = dot(X,PX) % E[X]EY = dot(Y,PY) % E[Y] VX = dot(X.^2,PX) - EX^2 % Var[X]VY = dot(Y.^2,PY) - EY^2 % Var[Y] disp(' Use array operations on matrices X, Y, PX, PY, t, u, and P')
Got questions? Get instant answers now!

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, Applied probability. OpenStax CNX. Aug 31, 2009 Download for free at http://cnx.org/content/col10708/1.6
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'Applied probability' conversation and receive update notifications?

Ask