Suppose the random vector (X,Y ) satisfies the regression model Y = m(X) + σ(X)ε, where m(·) = E(Y |·) belongs to some parametric class {mθ(·) : θ ∈ Θ} of regression functions, σ2(·) = Var(Y |·) is unknown, and ε is independent of X. The response Y is subject to random right censoring, and the covariate X is completely observed. A new estimation procedure for the true, unknown parameter vector ...

Calculating summary statistics such as the mean, standard deviation, and an upper confidence limit on the mean is straightforward when the data values are known. However, environmental data often are reported from the analytical laboratory as left censored, meaning the actual concentration for a given contaminant was not detected above the method detection limit. Therefore, the true concentrati...

This work develops a Bayesian approach to perform inference and prediction in Gaussian random fields based on spatial censored data. These type of data occur often in the earth sciences due either to limitations of the measuring device or particular features of the sampling process used to collect the data. Inference and prediction on the underlying Gaussian random field is performed, through d...

We analyze households' joint investment decisions for nancial wealth and homes. We use a bivariate censored regression model with endogenous switching. Fixed costs or transaction costs are captured by an unobserved nonzero censoring threshold. The model allows for spill{over e ects of a binding threshold for one asset on the demand for the other asset. We nd that tenure choice a ects the level ...

Doubly interval-censored failure time data refer to the failure time data where the survival time of interest is defined as the elapsed time between two related events. Furthermore, observations on the occurrences of both events could be rightor interval-censored. One field in which such data often occur is epidemiological studies where the two events may represent infection and subsequent onse...

In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data. We utilize data augmentation metho...

We propose a non-parametric multiple imputation scheme, NPMLE imputation, for the analysis of interval censored survival data. Features of the method are that it converts interval-censored data problems to complete data or right censored data problems to which many standard approaches can be used, and that measures of uncertainty are easily obtained. In addition to the event time of primary int...

SUMMARY Nonparametric Bayesian inference using bathtub hazard rates in survival analysis is developed. A new simulation method, Auxiliary Random Functions, is introduced. When used within a Gibbs sampler, this method enables a uniied treatment of exact, right-censored, left-censored, left-trucated and interval censored data, with and without covariates. The models and methods are exempliied via...

This study proposes an approach based on neural networks to perform the analysis of the censored data. Two neural networks are constructed: the first neural network is designed to estimate the censored data by means of constructing the model derived from the uncensored data and, the second neural network is designed to obtain the optimum parameter settings of control factors by using the uncens...