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This paper addresses the estimation of the nonparametric conditional moment restricted model that involves an infinite-dimensional parameter g0. We estimate it in a quasi-Bayesian way, based on the limited information likelihood, and investigate the impact of three types of priors on the...
Persistent link: https://www.econbiz.de/10015232003
This paper addresses the estimation of the nonparametric conditional moment restricted model that involves an infinite-dimensional parameter g0. We estimate it in a quasi-Bayesian way, based on the limited information likelihood, and investigate the impact of three types of priors on the...
Persistent link: https://www.econbiz.de/10011113752
We consider an approximate posterior approach to making joint probabilistic inference on the action and the associated risk in data mining. The posterior probability is based on a profile empirical likelihood, which imposes a moment restriction relating the action to the resulting risk, but does...
Persistent link: https://www.econbiz.de/10014186158
This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information likelihood. The posterior distribution converges to zero...
Persistent link: https://www.econbiz.de/10013108660
Persistent link: https://www.econbiz.de/10011121301
Hoeffding’s inequality provides a probability bound for the deviation between the average of n independent bounded random variables and its mean. This paper introduces two inequalities that extend Hoeffding’s inequality to panel data, which consists of several mutually independent sequences...
Persistent link: https://www.econbiz.de/10011040061
Persistent link: https://www.econbiz.de/10006627274
As a generalization of the accelerated failure time models, we consider parametric models of lifetime Y, where the conditional mean E(Y|X;beta) can depend nonlinearly on the covariates X and some parameters beta. The error distribution can be heteroscedastic and dependent on X. With observed...
Persistent link: https://www.econbiz.de/10005752613
This paper considers the problem of predicting binary choices by selecting from a possibly large set of candidate explanatory variables, which can include both exogenous variables and lagged dependent variables. We consider risk minimization with the risk function being the predictive...
Persistent link: https://www.econbiz.de/10008506423
Jiang and Tanner (2008) consider a method of classification using the Gibbs posterior which is directly constructed from the empirical classification errors. They propose an algorithm to sample from the Gibbs posterior which utilizes a smoothed approximation of the empirical classification...
Persistent link: https://www.econbiz.de/10008488296