filter

Re-estimate factors by Kalman filtering data taking Dynamo coefficients as given

## Syntax

 [outputDb, a, info] = kalmanFilter(a, inputDb, range, ___)

## Input arguments

a [ Dynamo ]

Estimated Dynamo object.

inputDb [ struct ]

Input database or tseries object with the

Dynamo observables.

range [ Dater ]

Filter date range.

## Output arguments

outputDb [ struct ]

Output databank.

a [ Dynamo ]

Dynamo object.

## Options

Cross=true [ true | false | numeric ]

Run the filter with the off-diagonal elements in the covariance matrix of idiosyncratic residuals; if false all cross-covariances are reset to zero; if a number between zero and one, all cross-covariances are multiplied by that number.

InvFunc="auto" [ "auto" | function_handle ]

Inversion method for the FMSE matrices.

MeanOnly=false [ true | false ]

Return only mean data, i.e. point estimates.

Persist=false [ true | false ]

If filter or forecast is used with Persist=true for the first time, the forecast MSE matrices and their inverses will be stored; subsequent calls of the filter or forecast functions will re-use these matrices until filter or forecast is called with this option set to false.

Tolerance=0 [ numeric ]

Numerical tolerance under which two FMSE matrices computed in two consecutive periods will be treated as equal and their inversions will be re-used, not re-computed.

## Description

It is the user's responsibility to make sure that filter and forecast called with Persist= set to true are valid, i.e. that the previously computed FMSE matrices can be really re-used in the current run.

## Example