This paper proposes the application of Gaussian process regression (GPR) as an alternative regression model to resolve the hard overlapped electrochemical signals belonging to the 2,4,6trichlorophenol/2,6-dichlorophenol (TCP/DCP) system. Gaussian process derives from the perspective of Bayesian non-parametric regression methods, in terms of the parameterization of the covariance function, resul...

Modeling data with multivariate count responses is a challenge problem due to the discrete nature of the responses. Such data are commonly observed in many applications such as biology, epidemiology and social studies. The existing methods for univariate count response cannot be easily extended to the multivariate situation since the dependency among multiple responses needs to be properly acco...

Additive tree methods are widely used in ecology. To date most ecologists have boosted regression (BRT) methods. However, Bayesian additive (BART) models may offer advantages to previously unexamined. Here we test whether BART has some benefits over the BRT method. do this use two grassland data and 13 hydroclimatic land predictor variables. The dataset contained from a period of drought as wel...

Suppose that X is a d-dimensional elliptically distributed random vector with dispersion matrix Σ . Many multivariate statistical methods like principal component analysis, canonical correlation analysis, linear discriminant analysis, and multivariate regression require the covariance or dispersion matrix of X only up to a scaling constant. Hence, the present work concentrates on the shape matr...

environmental management and planning and benefiting from climatic capacities of every geographical place are related to homogenous climatic regions and the most influential climatic elements in spatial separation of the climatic regions. accordingly, the aim of the present study includes determining the most influential climatic elements affecting on the climate of esfahan province, and the sp...