Modeling nonstationary temperature maxima based on extremal dependence changing with event magnitude

extremal region detection guided by maxima of gradient magnitude

a problem of computer vision applications is to detect regions of interest under dif- ferent imaging conditions. the state-of-the-art maximally stable extremal regions (mser) detects affine covariant regions by applying all possible thresholds on the input image, and through three main steps including: 1) making a component tree of extremal regions’ evolution (enumeration), 2) obtaining region ...

Functional Modeling of Iranian Precipitation Based on Temperature and Humidity

Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Modeling of Iranian precipitation based on temperature and humidity with continuous the essential nature of such phenomena that are continuous functions of time has not been done properly. The corresponding data are generally collected daily or ...

On extremal dependence of block vectors

Dependence of Spectroscopic Properties of Copper Oxide Based Silica Supported Nanostructure on Temperature

Various concentrations of copper were embedded into silica matrix to xerogel forms using copper source Cu(NO3)2∙3H2O. The xerogel samples were prepared by hydrolysis and condensation of Tetraethyl Ortho-Silicate (TEOS) with determination of new molar ratio of the components by the sol-gel method. After ambient drying, the xerogel samples were heated from 60 to 1000˚C at a slow heating rate (50°...

Multivariate dependence modeling based on comonotonic factors

Comonotonic latent variables are introduced into general factor models, in order to allow non-linear transformations of latent factors, so that various multivariate dependence structures can be captured. Through decomposing each univariate marginal into several components, and letting some components belong to different sets of comonotonic latent variables, a great variety of multivariate model...