Exponential parametric distortion nonlinear measurement errors Models

Nonlinear Models of Measurement Errors

Measure errors in economic data are pervasive and nontrivial in size. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in economic analysis. The importance of measurement errors in analyzing the empirical implications of economic theories is highlighted in Milton Friedman’s seminal book on the consumption...

Nonlinear Models of Measurement Errors By

Partial linear single index models with distortion measurement errors

We study partial linear single index models when the response and the covariates in the parametric part are measured with errors and distorted by unknown functions of commonly observable confounding variables, and propose a semiparametric covariate-adjusted estimation procedure. We apply the minimum average variance estimation method to estimate the parameters of interest. This is different fro...

Bayesian inference of exponential random graph models under measurement errors

While the impact of measurement errors inherent in network data has been widely recognized, relatively little work has been done to solve the problem mainly due to the complex dependence nature of network data. In this paper, we propose a Bayesian inference framework for summary statistics of the true underlying network, based on the network observed with measurement errors. To the best of our ...

Parametric Measurement Error Models

We describe a simulation-based method of inference for parametric measurement error models in which the measurement error variance is known or at least well estimated. The method entails adding additional measurement error in known increments to the data, computing estimates from the contaminated data, establishing a trend between these estimates and the variance of the added errors, and extrap...