Kalman smoother
[betas,sigmas]=smoothing(F,betat,betaf,sigmat,sigmaf, begsmooth)
* F = transition matrix
* betat = vector of filtered beta at date t with the information available at date t (beta(t|t))
* betaf = vector of filtered beta at date t with the information available at date t-1 (beta(t|t-1)
* sigmat = vector of filtered variances at date t with the information available at date t (sigma(t|t))
* sigmat = vector of filtered variances at date t with the information available at date t-1 (sigma(t|t-1))
* begsmooth = first observation where to calculate smoothed values
* betas = vector of smoothed beta at date t with the information available at date T (beta(t|T)
* sigmat = vector of smoothed variances at date t with the information available at date T (sigma(t|T))
// smoothing is a used by the function kalman: [betas,sigmats]=smooth(grocer_F,betat,betaf,sigmatt,sigmatf) | ![]() | ![]() |