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See the recommended documentation of this function

corr

correlation, covariance

Calling Sequence

```[cov,Mean]=corr(x,[y],nlags)
[cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)

[w,xu]=corr('updt',x1,[y1],w0)
[w,xu]=corr('updt',x2,[y2],w,xu)
...
[wk]=corr('updt',xk,[yk],w,xu)```

Arguments

x

a real vector

y

a real vector, default value x.

nlags

integer, number of correlation coefficients desired.

xmacro

a scilab external (see below).

ymacro

a scilab external (see below), default value xmacro

n

an integer, total size of the sequence (see below).

sect

size of sections of the sequence (see below).

xi

a real vector

yi

a real vector,default value xi.

cov

real vector, the correlation coefficients

Mean

real number or vector, the mean of x and if given y

Description

Computes

```n - m
====
\                                       1
cov(m) =  >   (x(k) - xmean) (y(m+k) - ymean) * ---
/                                       n
====
k = 1```

for m=0,..,`nlag-1` and two vectors `x=[x(1),..,x(n)]` `y=[y(1),..,y(n)]`

Note that if x and y sequences are differents corr(x,y,...) is different with corr(y,x,...)

Short sequences

`[cov,Mean]=corr(x,[y],nlags)` returns the first nlags correlation coefficients and Mean = `mean(x)` (mean of `[x,y]` if `y` is an argument). The sequence `x` (resp. `y`) is assumed real, and `x` and `y` are of same dimension n.

Long sequences

`[cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)` Here `xmacro` is either

• a function of type `[xx]=xmacro(sect,istart)` which returns a vector `xx` of dimension `nsect` containing the part of the sequence with indices from `istart` to `istart+sect-1`.

• a fortran subroutine or C procedure which performs the same calculation. (See the source code of `dgetx` for an example). `n` = total size of the sequence. `sect` = size of sections of the sequence. `sect` must be a power of 2. `cov` has dimension `sect`. Calculation is performed by FFT.

Updating method
```[w,xu]=corr('updt',x1,[y1],w0)
[w,xu]=corr('updt',x2,[y2],w,xu)
...
wk=corr('updt',xk,[yk],w,xu)```

With this calling sequence the calculation is updated at each call to `corr`.

```w0 = 0*ones(1,2*nlags);
nlags = power of 2.```

`x1,x2,...` are parts of `x` such that `x=[x1,x2,...]` and sizes of `xi` a power of 2. To get `nlags` coefficients a final fft must be performed `c=fft(w,1)/n`; `cov=c(1nlags)` (`n` is the size of `x (y)`). Caution: this calling sequence assumes that `xmean = ymean = 0`.

Examples

```x=%pi/10:%pi/10:102.4*%pi;
rand('seed');rand('normal');
y=[.8*sin(x)+.8*sin(2*x)+rand(x);.8*sin(x)+.8*sin(1.99*x)+rand(x)];
c=[];
for j=1:2,for k=1:2,c=[c;corr(y(k,:),y(j,:),64)];end;end;
c=matrix(c,2,128);cov=[];
for j=1:64,cov=[cov;c(:,(j-1)*2+1:2*j)];end;
rand('unif')

rand('normal');x=rand(1,256);y=-x;
deff('[z]=xx(inc,is)','z=x(is:is+inc-1)');
deff('[z]=yy(inc,is)','z=y(is:is+inc-1)');
[c,mxy]=corr(x,y,32);
x=x-mxy(1)*ones(x);y=y-mxy(2)*ones(y);  //centring
c1=corr(x,y,32);c2=corr(x,32);
norm(c1+c2,1)
[c3,m3]=corr('fft',xx,yy,256,32);
norm(c1-c3,1)
[c4,m4]=corr('fft',xx,256,32);
norm(m3,1),norm(m4,1)
norm(c3-c1,1),norm(c4-c2,1)
x1=x(1:128);x2=x(129:256);
y1=y(1:128);y2=y(129:256);
w0=0*ones(1:64);   //32 coeffs
[w1,xu]=corr('u',x1,y1,w0);w2=corr('u',x2,y2,w1,xu);
zz=real(fft(w2,1))/256;c5=zz(1:32);
norm(c5-c1,1)
[w1,xu]=corr('u',x1,w0);w2=corr('u',x2,w1,xu);
zz=real(fft(w2,1))/256;c6=zz(1:32);
norm(c6-c2,1)
rand('unif')

// test for Fortran or C external
//
deff('[y]=xmacro(sec,ist)','y=sin(ist:(ist+sec-1))');
x=xmacro(100,1);
[cc1,mm1]=corr(x,2^3);
[cc,mm]=corr('fft',xmacro,100,2^3);
[cc2,mm2]=corr('fft','corexx',100,2^3);
[max(abs(cc-cc1)),max(abs(mm-mm1)),max(abs(cc-cc2)),max(abs(mm-mm2))]

deff('[y]=ymacro(sec,ist)','y=cos(ist:(ist+sec-1))');
y=ymacro(100,1);
[cc1,mm1]=corr(x,y,2^3);
[cc,mm]=corr('fft',xmacro,ymacro,100,2^3);
[cc2,mm2]=corr('fft','corexx','corexy',100,2^3);
[max(abs(cc-cc1)),max(abs(mm-mm1)),max(abs(cc-cc2)),max(abs(mm-mm2))]```