We develop a generalized method of moments (GMM) approach for fast parameter estimation in a new class of Dirichlet latent variable models with mixed data types. Parameter estimation via GMM has been demonstrated to have computational and statistical advantages over alternative methods, such as expectation maximization, variational inference, and Markov chain Monte Carlo. The key computational ...

In this paper we propose a class of efficient Generalized Method-of-Moments (GMM) algorithms for computing parameters of the Plackett-Luce model, where the data consists of full rankings over alternatives. Our technique is based on breaking the full rankings into pairwise comparisons, and then computing parameters that satisfy a set of generalized moment conditions. We identify conditions for t...

In this paper we propose a class of efficient Generalized Method-of-Moments (GMM) algorithms for computing parameters of the Plackett-Luce model, where the data consists of full rankings over alternatives. Our technique is based on breaking the full rankings into pairwise comparisons, and then computing parameters that satisfy a set of generalized moment conditions. We identify conditions for t...

I propose a nonparametric iid bootstrap that achieves asymptotic refinements for t tests and confidence intervals based on the generalized method of moments (GMM) estimators even when the model is misspecified. In addition, my bootstrap does not require recentering the bootstrap moment function, which has been considered as a critical procedure for bootstrapping GMM. The elimination of the rece...

We compared recumbent bicycle kinetics in diabetic peripheral neuropathy and nondiabetic men (nine per group). 3D kinematic and force pedal data in a linked-segment model were used. The generalized muscle moment (GMM) patterns were similar between the two groups except for (1) decreased maximum knee flexor moment, (2) increased minimum knee flexor GMM, and (3) maximum hip extensor GMM by the di...

this study is an attempt to develop a model of the simultaneous structure of the aggregate dynamic supply and demand to be used for estimation of parameters from data related to iran’s economy. the method for developing the model is an application of the dynamic and simultaneous process of aggregate supply and demand. obtained differential equations are used for solve the model. to estimate the...

This paper considers optimal testing of model comparison hypotheses for misspeci…ed unconditional moment restriction models. We adopt the generalized Neyman-Pearson optimality criterion, which focuses on the convergence rates of the type I and II error probabilities under …xed global alternatives, and derive an optimal but practically infeasible test. We then propose feasible approximation test...

This paper investigates finite sample properties of localized version of moment estimator including Local Generalized Method of Moments(LGMM) and conditional Euclidean Empirical Likelihood(CEEL) estimator. By comparing the performance of LGMM estimator and C-EEL estimator with various nonparametric techniques including the choice of bandwidth, choice of kernel and trimming strategies, this pape...