## doc: gp_inf

Bayesian system resolution for computing posterior of GP given the observations *Yt* at *Xt*

### Syntax

BayesInv = gp_inf(Ktt, Yt, noise)
BayesInv = gp_inf(Ktt, Yt, noise, Ht)

### Arguments

*Ktt* matrix *(nt, nt)* of kernel between the points of *Xt**Yt* vector *(nt, 1)* of observations*noise* noise standard deviation *Ht* matrix *(nt, b)* of basis data as returned by *basis_cst(Xt)*

### Outputs

struct array containing:

*RC* upper triangular matrix *(nt,nt)* of Cholesky decomposition of *Ktt+noise*I**invCY* vector *(nt,1)* solution of *beta* vector *(b,1)* solution of the basis system

### See also

gp_pred | gp_inf_update