Statistical Computing
Investigating the Effective Factors on Adoption of E-Learning System in Qazvin University of Medical Sciences

Hassan Rashidi; Hamed Heidari; Marzie Movahedin; Maryam Moazami Gudarzi; Mostafa Shakerian

Volume 1, Issue 2 , June 2023, Pages 1-27

https://doi.org/10.22054/jcsm.2019.43349.1017

Abstract
  The purpose of this research is to identify and introduce effective factors in adoption of e-learning based on technology adoption model. Accordingly, by considering the studies conducted in this field, several variables such as computer self-efficacy, content quality, system support, interface design, ...  Read More

Mathematical Computing
Some Theoretical Results on the Tensor Elliptical Distribution

Mohammad Arashi

Volume 1, Issue 2 , June 2023, Pages 29-41

https://doi.org/10.22054/jcsm.2021.47404.1019

Abstract
  The multilinear normal distribution is a widely used tool in the tensor analysis of magnetic resonance imaging (MRI). Diffusion tensor MRI provides a statistical estimate of a symmetric 2nd-order diffusion tensor for each voxel within an imaging volume. In this article, tensor elliptical (TE) distribution ...  Read More

Statistical Computing
Assessment and Modeling of Interval-Valued Variables in Generalized Linear Models

farzad eskandari

Volume 1, Issue 2 , June 2023, Pages 43-70

https://doi.org/10.22054/jcsm.2021.52523.1020

Abstract
  Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable ...  Read More

Estimation for the Reliability Characteristics of a Family of Lifetime Distributions under Progressive Censoring

Alireza Safariyan; Reza Arabi Belaghi

Volume 1, Issue 2 , June 2023, Pages 71-86

https://doi.org/10.22054/jcsm.2021.53672.1021

Abstract
  In this paper, the probability of failure-free operation until time t, along with the probability of stress-strength, based on progressive censoring data is studied in a family of lifetime distributions. Since the number of data in a progressive censoring scheme is usually reduced, so shrinkage methods ...  Read More

Bayesian Network
A Simple Gibbs Sampler for Learning Bayesian Network Structure

Vahid Rezaei Tabar

Volume 1, Issue 2 , June 2023, Pages 87-97

https://doi.org/10.22054/jcsm.2021.55657.1022

Abstract
  The aim of this paper is to learn a Bayesian network structure for discrete variables. For this purpose, we introduce a Gibbs sampler method. Each sample represents a Bayesian network. Thus, in the process of Gibbs sampling, we obtain a set of Bayesian networks. For achieving a single graph that represents ...  Read More

Statistical Simulation
Estimation of Fixed Parameters in Negative Binomial Mixed Model Using Shrinkage Estimators

Zahra Zandi; Hossein Bevrani; Reza Arabi Belaghi

Volume 1, Issue 2 , June 2023, Pages 99-124

https://doi.org/10.22054/jcsm.2021.56488.1023

Abstract
  ‎In this paper‎, ‎we consider the problem of parameter estimation in {color{blue} negative binomial mixed model} when it is suspected that some of the fixed parameters may be restricted to a subspace via linear shrinkage‎, ‎{color{blue} preliminary test}‎, ‎shrinkage {color{blue} ...  Read More

Mathematical Computing
Mathematical Modeling of Behavior of Retrofitted RC Frames

Ali Moafi; Ali Kheyroddin; Hamid Saberi; Vahid Saberi

Volume 1, Issue 2 , June 2023, Pages 125-138

https://doi.org/10.22054/jcsm.2021.59910.1024

Abstract
  Due to several reasons as the low resistance of constructed concrete and also change in codes or application of structures, some concrete frames need to be retrofitted. By adding the steel prop and curb to the reinforced concrete, many parameters are changed such as ductility, resistance, and stiffness. ...  Read More

Mathematical Computing
New ‎Adaptive Monte Carlo Algorithm ‎t‎o Solve ‎Financial‎ Option ‎Pricing Problems‎

Mahboubeh Aalaei

Volume 1, Issue 2 , June 2023, Pages 139-151

https://doi.org/10.22054/jcsm.2021.60573.1025

Abstract
  In this paper, a new adaptive Monte Carlo algorithm is proposed to solve ‎the ‎systems ‎of ‎linear ‎algebraic ‎equations ‎arising ‎from‎ the Black–Scholes model ‎to ‎price‎ European and American options. The proposed algorithm offers several advantages ...  Read More

Routing Optimization in Wireless Sensor Networks to Increase Network Life by Managing Network Energy

bahareh asadi

Volume 1, Issue 2 , June 2023, Pages 153-169

https://doi.org/10.22054/jcsm.2022.64359.1029

Abstract
  One of the important challenges in Wireless Sensor Networks is to proceeds data transmission in a way that tries to increase the life of the network. One of the main issues is the reduction of latency in the node and energy in the sink nodes. Due to the limited energy of the nodes, data transmission ...  Read More

Semiparametric Models in Finite Mixture of Negative Binomial Responses

sima naghizadeh

Volume 1, Issue 2 , June 2023, Pages 171-190

https://doi.org/10.22054/jcsm.2022.66414.1031

Abstract
  Abstract: so many natural phenomena of determining relationship and the effect of input variables on response variable in statistical studies may be different from the suggested model that the researcher selects for his study due to the occupant exists in the structure of data. It may be so influential ...  Read More

Static Sign Language Recognition Using Depth Data Based on Geometric Features

Zahra Aghajani; mostafa karbasi; Bahareh asadi

Volume 1, Issue 2 , June 2023, Pages 191-203

https://doi.org/10.22054/jcsm.2022.63486.1028

Abstract
  Deaf people or people with hearing loss have a major problem in everyday communication. There are many applications available in the market to help blind people to interact with the world. Voice-based email and chatting systems are available to communicate with each other by blinds. This helps to interact ...  Read More

A Bayesian Semiparametric Random Effect Model for Meta-Regression

Ehsan Ormoz

Volume 1, Issue 2 , June 2023, Pages 205-223

https://doi.org/10.22054/jcsm.2022.69925.1032

Abstract
  In this paper, we will introduce a Bayesian semiparametric model concerned with both constant and coefficients. In Meta-Analysis or Meta-Regression, we usually use a parametric family. However, lately the increasing tendency to use Bayesian nonparametric and semiparametric models, entered this area too. ...  Read More