The maximum spacing estimation for multivariate observations

The Maximum Spacing Estimation for Multivariate Observations

For i.i.d. univariate observations a new estimation method, the maximum spacing (MSP) method, was defined in Ranneby (1984) and independently by Cheng and Amin (1983). The idea behind the method, as described by Ranneby (1984), is to approximate the Kullback-Leibler information so each contribution is bounded from above. In the present paper the MSP-method is extended to multivariate observatio...

Maximum likelihood estimation for multivariate mixture observations of markov chains

Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains

In this paper a framework for maximum a posteriori (MAP) estimation of hidden Markov models (HMM) is presented. Three key issues of MAP estimation, namely the choice of prior distribution family, the specification of the parameters of prior densities and the evaluation of the MAP estimates, are addressed. Using HMMs with Gaussian mixture state observation densities as an example, it is assumed ...

MIVQUE and Maximum Likelihood Estimation for Multivariate Linear Models with Incomplete Observations

The problem of estimating the parameters of multivariate linear models in the context of an arbitrary pattern of missing data is addressed in the present paper. While this problem is frequently handled by EM strategies, we propose a Gauss-Markov approach based on an initial linearization of the covariance of the model. A complete class of quadratic estimators is first exhibited in order to deri...

Outlier test for a group of multivariate observations

Assume that we have m independent random samples each of size n from Np(; ) and our goal is to test whether or not the ith sample is an outlier (i=1,2,…..m). To date it is well known that a test statistics exist whose null distribution is Betta and given the relationship between Betta and F distribution, an F test statistic can be used. In the statistical literature however a clear and preci...