This chapter reviews work by the authors on the multicriteria Flexible Least Squares (FLS) approach to model estimation. Related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm

A Fortran implementation for the "Flexible Least Squares" (FLS) method for time-varying linear regression (FLS-TVLR) is discussed. The latest Fortran implementation for FLS-TVLR, along with tutorials and research publications, can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm

This article discusses the use of associative memories for obtaining preliminary parameter estimates for nonlinear systems. Annotated pointers to related work can be accessed at http://www.econ.iastate.edu/tesfatsi/vita.htm#MAM

An exact procedure is developed for sequentially updating the optimal solution for a general discrete-time nonlinear least-squares estimation problem as the process length increases and new observations are obtained. The optimal sequential estimation equations are derived by means of an...

This article appeared in Computer Science in Economics and Management (now Computational Economics). Parameter estimation problems for nonlinear systems are typically formulated as nonlinear optimization problems. For such problems, one has the usual difficulty that standard successive...

This study develops a general multicriteria Flexible Least Squares (FLS) framework for the sequential estimation of process states. Three well-known state estimation algorithms (the Viterbi, Larson-Peschon, and Kalman filters) are derived as monocriterion specializations. The FLS framework is...

This study uses the Flexible Least Squares method for Time-Varying Linear Regression (FLS-TVLR) to investigate coefficient stability for the Goldfeld U.S. money demand model over the volatile period 1959:Q2 to 1985:Q3. The only constraint imposed on coefficient variation over time is a...

This study considers why multicriteria techniques have not been widely adopted in econometrics to date. It then presents a multicriteria approach to estimation problems for which the basic objective is to learn about the sequence of states through which a process has passed. The multicriteria...

This study proposes a Flexible Least Squares (FLS) method for state estimation when the dynamic equations are unknown but the process state evolves only slowly over time. A smoothness prior is introduced in place of an explicit specification for the unknown dynamic equations governing the...

A "flexible least cost method" is proposed for investigating the basic compatibility of theory and observations in the absence of valid or known stochastic characterizations for residual error terms. Annotated pointers to related work can be accessed here:...