the purpose of this study is estimation of daily value at risk (var) for total index of tehran stock exchange using parametric, nonparametric and semi-parametric approaches. conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated var and also to compare the performance of mentioned approaches. in most cases, based on backtesting statistics results, ...

in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...

In the current study, the kinetics of asphaltene particle flocculation is investigated under a shear flow through numerical simulation. The discrete element method (DEM) is coupled with computational fluid dynamics (CFD) to model the agglomeration and fragmentation processes. In addition, a coalescence model is proposed to consider the attachment of colliding particles. The changes in mean asph...

Hydrological processes and their spatial distribution directly are relevant to climate, topography, geology, and land use in the watershed. Therefore, use of a model whit integrity and high performance for simulating the process in deferent watersheds is very important. In this study was assessment performance of semi-distributed SWAT model in simulating hydrology processes in three watersheds ...

In this paper it will show how unknown density and distribution functions can be modeled semi-nonparametrically via orthonormal series expansions, and how to estimate semi-nonparametric (SNP) models via a sieve estimation approach. As an application I will focus on the mixed proportional hazard (MPH) model with fixed right censoring and unspecified mixing distribution and baseline hazard. I wil...

Segmentation and labeling of high dimensional time series data has wide applications in behavior understanding and medical diagnosis. Due to the difficulty of obtaining a large amount the label information, realizing this objective in an unsupervised way is highly desirable. Hidden Semi-Markov Model (HSMM) is a classical tool for this problem. However, existing HSMM and its variants typically m...

Vehicle routing problem is a kind of common problem in logistics distribution center, in order to solve the high delivery cost of VRP and time constraint problem, the VRP model with the object level and constraints by semi-soft time window is built. Aiming to the semi-soft time window constraints the optimization of the model is discussed. Finally the numerical examples prove the superiority of...