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In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models.Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable.
The EM algorithm consists of two steps: the E-step and the M-step. Firstly, the model parameters and the () can be randomly initialized. In the E-step, the algorithm tries to guess the value of () based on the parameters, while in the M-step, the algorithm updates the value of the model parameters based on the guess of () of the E-step.
Policy analysis or public policy analysis is a technique used in the public administration sub-field of political science to enable civil servants, nonprofit organizations, and others to examine and evaluate the available options to implement the goals of laws and elected officials.
In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator used to estimate dynamic models of panel data.It was proposed in 1991 by Manuel Arellano and Stephen Bond, [1] based on the earlier work by Alok Bhargava and John Denis Sargan in 1983, for addressing certain endogeneity problems. [2]
Model selection can be performed with the GEE equivalent of the Akaike Information Criterion (AIC), the quasi-likelihood under the independence model criterion (QIC). [ 8 ] Relationship with Generalized Method of Moments
The eightfold path is a method of policy analysis assembled by Eugene Bardach, a professor at the Goldman School of Public Policy at the University of California, Berkeley. [1] It is outlined in his book A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving , which is now in its seventh edition. [ 2 ]
A typical finite-dimensional mixture model is a hierarchical model consisting of the following components: . N random variables that are observed, each distributed according to a mixture of K components, with the components belonging to the same parametric family of distributions (e.g., all normal, all Zipfian, etc.) but with different parameters
Unwarranted variations in medical practice refer to the differences in care that cannot be explained by the illness/medical need or by patient preferences. The term “unwarranted variations” was first coined by Dr. John Wennberg when he observed small area (geographic) and practice style variations, which were not based on clinical rationale. [5]