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# weib2dstatplot

## PURPOSE

Computes and plots the conditional mean and standard deviation

## SYNOPSIS

[ax11, h11, h22 ]=weib2dstatplot(V,H,phat,res,varargin)

## DESCRIPTION

```  WEIB2DSTATPLOT Computes and plots the conditional mean and standard deviation

CALL: weib2dstatplot(x1,x2,phat,res,sym);

x1,x2 = data
phat  = [A1 B1 A2 B2 C12], i.e., 2D weibull parameters.
res   = resolution (default range(X2)/12)
sym   = {s1,s2,s3,s4} cell array of plot symbols for
plotting empirical mean and standard deviation and
theoretical mean and standard deviation, respectively.
(default {'bo','rx','b-','r--'})

WEIB2DSTATPLOT plots the  empirical conditional mean and standard
deviation of X1 given X2 and optionally compares it with
a 2D weibull distribution with parameters given in phat.

Example
phat = [1 2 1.5 1 .8];
[y1,y2] = weib2drnd(phat,1000,1);
weib2dstatplot(y1,y2,phat);

## CROSS-REFERENCE INFORMATION

This function calls:
 range Calculates the difference between the maximum and minimum values. weib2dstat Mean and variance for the 2D Weibull distribution error Display message and abort function. gca Get handle to current axis. hold Hold current graph. iscell True for cell array. ishold Return hold state. linspace Linearly spaced vector. mean Average or mean value. nan Not-a-Number. plot Linear plot. std Standard deviation. title Graph title. xlabel X-axis label.
This function is called by:

## SOURCE CODE

```001 function [ax11, h11, h22  ]=weib2dstatplot(V,H,phat,res,varargin)
002 % WEIB2DSTATPLOT Computes and plots the conditional mean and standard deviation
003 %
004 %   CALL: weib2dstatplot(x1,x2,phat,res,sym);
005 %
006 %      x1,x2 = data
007 %      phat  = [A1 B1 A2 B2 C12], i.e., 2D weibull parameters.
008 %      res   = resolution (default range(X2)/12)
009 %      sym   = {s1,s2,s3,s4} cell array of plot symbols for
010 %              plotting empirical mean and standard deviation and
011 %              theoretical mean and standard deviation, respectively.
012 %              (default {'bo','rx','b-','r--'})
013 %
014 % WEIB2DSTATPLOT plots the  empirical conditional mean and standard
015 % deviation of X1 given X2 and optionally compares it with
016 % a 2D weibull distribution with parameters given in phat.
017 %
018 % Example
019 %  phat = [1 2 1.5 1 .8];
020 %  [y1,y2] = weib2drnd(phat,1000,1);
021 %  weib2dstatplot(y1,y2,phat);
022 %
024
025 % tested on matlab 5.2
026 % history:
027 % revised pab 03.11.2000
028 % changed var(tmp) to std(tmp)^2
029 % by Per A. Brodtkorb 23.11.98
030
031 %default values
032 sym = {'bo','rx','b-','r--'}; % default plot symbols for the empirical
033                               % mean and std, and theoretical mean and
034                               % std,respectivel
035
036 error(nargchk(2,8,nargin))
037 if nargin<4|isempty(res),   res=range(H(:))/12; end
038 Np=min(length(varargin),4);
039 if Np>0,
040   if Np>1
041     sym(1:Np)=varargin(1:Np);
042   elseif iscell(varargin{1}),
043     Np= min(length(varargin{1}),4);
044     sym(1:Np)=varargin{1}(1:Np);
045   end
046 end
047 grp=floor(H/res)+1; % dividing the data into groups
048 Ngrp=max(grp);
049 Nmesh=40;
050 h1=linspace(res/2, (Ngrp-0.5)*res, Ngrp)';
051 %v1=linspace(eps,max(V),Nmesh)';
052 h2=linspace(0, max(H), Nmesh)';
053
054
055 m=h1;v=h1;
056 for ix=1:Ngrp,
057   tmp=V(grp==ix);%find data in group number ix
058
059   if length(tmp)>max(4,0),% if less than 4 observations in the group
060     m(ix)=mean(tmp);
061     v(ix)=std(tmp).^2;
062   else
063     m(ix)=NaN;
064     v(ix)=NaN;
065   end
066 end
067
068 ih = ishold;
069 plot(h1,m,sym{1},h1,sqrt(v),sym{2});  hold on
070 if ~isempty(phat),
071   [M1 V1]= weib2dstat(phat,2,h2);
072   plot(h2,M1,sym{3},h2,sqrt(V1),sym{4}),
073 end
074 if ~ih, hold off,end
075
076 title('Conditional mean and standard deviation')
077 xlabel('x2')
078 if nargout>0
079   ax11=gca;
080 end
081```

Mathematical Statistics
Centre for Mathematical Sciences
Lund University with Lund Institute of Technology

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