空间误差分析：统一的应用导向处理（Matlab代码实现）
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💥1 概述
本文关于一维、二维和三维空间误差测量的研究。
📚2 运行结果
部分代码：
clear
ic=2; % skip step 1
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ic==1
% part I
% use y=sqrt(x/n), x has chi-square distribution with deg n
clear global n p
global n p
q=[0.5 .8 .9 .95];
l=[(0.1:0.025:0.2) (0.3:.1:.9) (1:9) (10:10:100)]';
NL = length(l);
NQ = length(q);
for jj=1:NQ
p=q(jj);
x =1; %initial guess for iteration
% x =0.01; %initial guess for fsolve
for ii=1:NL
n=l(ii);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% use fsolve from optimization toolbox %%
%% xs=fsolve('x2disc2',x);
%% xo= xs;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%% iteration %%%%%%%%%%%%
p0=x2cdf(x);
for j=1:2:9
while (p0 > p)
x=x-(0.1)^j;
p0=x2cdf(x);
end
while (p0 < p)
x=x+(0.1)^j;
p0=x2cdf(x);
end
end
xo=x;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
r(ii,jj)=sqrt(xo/n)
pause
end
end
DAT =[l r];
save \\mfile\\chi.mat l r
fname='chi.dat'
fid=fopen(fname,'wt')
fprintf(fid,'%8.2f %8.4f %8.4f %8.4f %8.4f\\n',DAT')
fclose(fid)
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ic==2
% part II
load chi.mat
NQ =4
adj= [ 0.7 0.5 0.15 -0.1];
semilogx(l,r)
xlabel('n')
ylabel(' R(p)/RMS ')
% title(' R(p)/RMS vs n, p=0.5, 0.8, 0.9, 0.95')
grid
for kk=1:NQ
if kk==1 p=0.5
elseif kk==2 p=0.8
elseif kk==3 p=0.9
elseif kk==4 p=0.95
end
text(.5,r(5,kk)+adj(kk),['p=' num2str(100*p) '%'])
end
axis('square')
figure(1)
pause
pf3('f62')
end
🎉3 参考文献
部分理论来源于网络，如有侵权请联系删除。
[1]David Hsu (2023). Spatial Error Analysis: A Unified Application-Oriented Treatment