We find a condition for the normalized sequence of independent and identically distriubted random nuclear operators to satisfy the Central Limit Theorem.

The Jordan Form of the VAR's Companion matrix is used for proving the equivalence between the statement that there are no jordan blocks of order two or higher in the Jordan matrix and the conditions of Granger's Representation Theorem for an I(1) series. Furthermore, a Diagonal polynomial matrix...

The application of nonlinear fixed effects models in econometrics has often been avoided for two reasons, one methodological, one practical. The methodological question centers on a incidental parametres problem that raises questions about the statistical properties of the estimator. The...

This paper studies the implementation of the coupling from the past (CFTP)method of Propp and Wilson (1996) in the set-up of two and three component mixtures with known components. We show that monotonicity structures can be exhibited in both cases, but that CFTP an still be costly for three...

In Van den Akker, Van Hoesel, and Savelsbergh (1994), we have studied a time-indexed formulation for single-machine scheduling problems and have presented a complete characterization of all facet inducing inequalities with right-hand side 1 and 2 for the convex hull of the monotone extension of...

This paper "tests" the performance of the approaches of Watson (1993), DeJong, Ingram and Whiteman (1996), Canova and De Nicolo (1995) and Ortega (1998) for evaluating stochastic dynamic general equilibrium models using Monte Carlo techniques. It asks: Do different model evaluation methodologies...

Likelihood ratio tests for restrictions on contegrating vectors are asymptotically X2 distributed. For some values of the parameters this asymptotic distribution does not give a good approximation to the finite sample distribution. In this paper we derive the Bartlett correction factor for the...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high frequency data on stock returns.

We decompose a stationary Markov process (X^t) as: X^t = a^o + [Sommation from j=1 to infinity) a^j Z^(j,t), where the Z^j 's processes admit ARMA specifications. These decompositions are deduced from a nonlinear canonical decomposition of the joint distribution of (X^t, X^(t-1)).

This paper deals with both exploration and interpretation problems related to posterior distributions for mixture models. The specification of mixture posterior distributions means that the presence of k! modes is known immediately.