Instead, we develop a multivariate model for ordinal ... for the thresholds and regression coefficients simultaneously. As a consequence, the variance–covariance matrix of the parameters can ...

Multivariate adaptive regression splines ... displayed in the form of BFs in MARS, may not be mutually exclusive. MARS automatically selects them based upon model improvement (2001).

Annals of Economics and Statistics, No. 123/124, SPECIAL ISSUE ON RECENT DEVELOPMENTS IN FINANCIAL ECONOMETRICS (December 2016), pp. 77-101 (25 pages) https://doi.org ...

We derive a closed form ... Multivariate Linear Filter to jointly estimate potential output, the natural rate of unemployment and the natural rate of interest, conditional on selected equilibrium ...

Investopedia / Eliana Rodgers The multivariate model is a popular statistical tool that uses multiple variables to forecast possible outcomes. Research analysts use multivariate models to forecast ...

In this paper we use Ching's multivariate Markov chain model to model the dependency of rating transitions of several credit entities. The model is an enhancement of the multivariate Markov chain ...

This paper proposes a multivariate Markov model for simulating the dynamics of correlated credit ratings of multiple firms. Our model is based on the single index model in modern portfolio theory and ...

Understanding one of the most important types of data analysis. by Amy Gallo You probably know by now that whenever possible you should be making data-driven decisions at work. But do you know how ...