Improved Generalized Method of Moment Estimators to Estimate Diffusion Models

Generalized Method of Moments Estimators and Identification

D espite Emerson’s contempt for foolish consistency, consistency is not a foolish property for an estimator. Indeed, its absence would seem troubling. Who would want to admit that his or her estimator wouldn’t get the right answer with “all the data in the world”? Consequently, a widely applicable method for devising consistent estimators is a useful tool. This section develops two such tools, ...

Projection Estimators for Generalized Linear Models

We introduce a new class of robust estimators for generalized linear models which is an extension of the class of projection estimators for linear regression. These projection estimators are defined using an initial robust estimator for a generalized linear model with only one unknown parameter. We found a bound for the maximum asymptotic bias of the projection estimator caused by a fraction ε ...

Efficient Estimators for Generalized Additive Models

Generalized additive models are a powerful generalization of linear and logistic regression models. In this paper we show that a natural regression graph learning algorithm efficiently learns generalized additive models. Efficiency is proven in two senses: the estimator’s future prediction accuracy approaches optimality at rate inverse polynomial in the size of the training data, and its runtim...

Improved estimators for constrained Markov chain models

Improved Measurements of RNA Structure Conservation with Generalized Centroid Estimators

Identification of non-protein-coding RNAs (ncRNAs) in genomes is a crucial task for not only molecular cell biology but also bioinformatics. Secondary structures of ncRNAs are employed as a key feature of ncRNA analysis since biological functions of ncRNAs are deeply related to their secondary structures. Although the minimum free energy (MFE) structure of an RNA sequence is regarded as the mos...