Conditional density estimation in measurement error problems

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Density estimation in the presence of heteroskedastic measurement error

We consider density estimation when the variable of interest is subject to heteroskedastic measurement error. The density is assumed to have a smooth but unknown functional form which we model with a penalized mixture of B-splines. We treat the situation where multiple mismeasured observations of each of the variables of interest are observed for at least some of the subjects, and the measureme...

متن کامل

Bottleneck Conditional Density Estimation

We propose a neural network framework for high-dimensional conditional density estimation. The Bottleneck Conditional Density Estimator (BCDE) is a variant of the conditional variational autoencoder (CVAE) that employs layer(s) of stochastic variables as the bottleneck between the input x and target y, where both are highdimensional. The key to effectively train BCDEs is the hybrid blending of ...

متن کامل

Density Estimation with Normal Measurement Error with Unknown Variance

Abstract: This paper deals with the problem of estimating a density based on observations which are contaminated by a normally distributed error whose variance is unknown. In the case of a completely unknown error variance, the impossibility of a uniformly consistent estimation is shown; however, a semi-uniformly consistent estimator is constructed under nonparametric smoothness conditions on t...

متن کامل

Fast Nonparametric Conditional Density Estimation

Conditional density estimation. The idea of conditional density estimation is to construct a density estimate f̂(y|x) for a dependent variable y, conditional on a vector of variables x. This can be seen as a generalization of regression, where instead of estimating the expected value E(y|x) alone, we instead model the full density. This is especially important for multi-modal densities, where th...

متن کامل

Partition-Based Conditional Density Estimation

We propose a general partition-based strategy to estimate conditional density with candidate densities that are piecewise constant with respect to the covariate. Capitalizing on a general penalized maximum likelihood model selection result, we prove, on two specific examples, that the penalty of each model can be chosen roughly proportional to its dimension. We first study a classical strategy ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Multivariate Analysis

سال: 2015

ISSN: 0047-259X

DOI: 10.1016/j.jmva.2014.08.011