This paper considers linear regression models when neither the response variable nor the
covariates can be directly observed, but are measured with multiplicative distortion …

We consider modal linear regression models when neither the response variable nor the
covariates can be directly observed, but are measured with multiplicative distortion …

Due to the ever more stringent environmental regulations focused on cleaner power
generation, thermal power plants that produce energy by burning fossil fuels are forced to …

This paper consider a new exponential parametric distortion measurement errors model for
the estimation of correlation coefficient between unobserved variables of interest. These …

This paper studies the estimation of correlation coefficient between unobserved variables of
interest. These unobservable variables are distorted in a multiplicative fashion by an …

In this paper, we proposed a parametric hypothesis test of the multiplicative distortion model
under the exponentially distributed but unobserved random variable. The unobservable …

We propose a covariance ratio measure for symmetry or asymmetry of a probability density
function. This measure is constructed by the ratio of the covariance connected with the …

We consider the estimation of Pearson correlation coefficient when two continuous variables
can not be directly observed but measured with multiplicative distortion measurement errors …

We propose a kernel density based estimation by constructing a nonparametric kernel
version of the maximum profile likelihood estimator for partial linear multivariate responses …

We consider the parameter estimation for multiplicative linear regression models with or
without multiplicative distortion measurement errors. For the latter, both the response …