Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions ...

When response outcomes are continuous error terms in models are normally distributed and a standard normal distribution function is adequate. The logistic distribution function which is very similar to the normal distribution function is required when the response variable is binary. Parameters of a logistic response function are often estimated using the method of maximum likelihood (ML). One ...

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits...

Biomedical research often involves the measurement of multiple outcomes in different scales (continuous, binary and ordinal). A common approach for the analysis of such data is to ignore the potential correlation among the outcomes and model each outcome separately. This can lead not only to loss of efficiency but also to biased estimates in the presence of missing data. We address the problem ...

Model averaging provides an alternative to model selection. An algorithm ARM rooted in information theory is proposed to combine di erent regression models/methods. A simulation is conducted in the context of linear regression to compare its performance with familiar model selection criteria AIC and BIC, and also with some Bayesian model averaging (BMA) methods. The simulation suggests the foll...

Wave overtopping at breakwaters is one of their essential hydraulic characteristics when determining the design crest level. This study concentrates on developing a new practical formula on predicting wave overtopping, by implementing two different statistical models, Multiple Linear Regression model (MLR) and Generalized Linear Regression model (GLM). The models consider dependency of overtopp...

evaporation is one of the main parameters for the optimum operation of reservoirs, design of irrigation systems and scientific management of water resources. accurate estimation of the water evaporation level is crucial in any region especially in arid and semiarid regions. in this study, the feasibility of simulation of pan evaporation in maraghe station using the multiple regression models we...