Multistage least-squares parameter estimation algorithms which are either recursive in the dimension of an assumed linear model, or both recursive in the model dimension and sequential in time are obtained. Different aspects of the following problems are considered. 1) Given a linear model,

, with

unknown parameters,

, and datum

, obtain least-square estimators (LSE\´s) which are recursive in the dimension of

. 2) Given the same conditions as in 1), a new measurement becomes available at time

, obtain a LSE for

which is both recursive in the dimension of

and sequential in

.