Conditional fiducial models

Conditional Logit Models

1 Conditional Graphical Models

In this chapter we propose a modification of CRF-like algorithms that allows for solving large-scale structured classification problems. Our approach consists in upper bounding the CRF functional in order to decompose its training into independent optimisation problems per clique. Furthermore we show that each sub-problem corresponds to solving a multiclass learning task in each clique, which e...

Exponential Conditional Volatility Models

The asymptotic distribution of maximum likelihood estimators is derived for a class of exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models. The result carries over to models for duration and realised volatility that use an exponential link function. A key feature of the model formulation is that the dynamics are driven by the score. Keywords: Duration models; g...

Conditional Point Distribution Models

In this paper, we propose an efficient method for drawing shape samples using a point distribution model (PDM) that is conditioned on given points. This technique is suited for sample-based segmentation methods that rely on a PDM, e.g. [6], [2] and [3]. It enables these algorithms to effectively constrain the solution space by considering a small number of user inputs – often one or two landmar...

Testing Conditional Factor Models∗

We develop a methodology for estimating time-varying alphas and factor loadings based on nonparametric techniques. We test whether conditional alphas and long-run alphas, which are averages of conditional alphas, are equal to zero and derive test statistics for the constancy of factor loadings. The tests can be performed for a single asset or jointly across portfolios. The traditional Gibbons, ...