Abstract Machine learning (ML) has been widely used in microbiome research for biomarker
selection and disease prediction. By training microbial profiles of samples from patients and …

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 …

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 considers nonlinear regression models when neither the response variable nor
the covariates can be directly observed, but are measured with both multiplicative and …

This paper considers partial linear single-index regression models when all the variables
are measured with multiplicative distortion measurement errors. To eliminate the effect …

In this paper, we mainly discuss the cure model with survival data. Different from the usual
survival data with right-censoring, we incorporate the features of left-truncation and …

In this paper, we propose a new identifiability condition by using the logarithmic calibration
for the multiplicative distortion partial linear measurement errors models, when neither the …

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

In this paper we consider partial linear regression models when all the variables are
measured with multiplicative distortion measurement errors. To eliminate the effect caused …