Statistical Computing
A Berry-Esseen Type Bound for a Smoothed Version of Grenander Estimator

Raheleh Zamini

Volume 1, Issue 1 , December 2022, , Pages 1-9

https://doi.org/10.22054/jcsm.2018.33790.1007

Abstract
  In various statistical model, such as density estimation and estimation of regression curves or hazardrates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametricstatistics is to estimate a monotone density function f on a compact interval. A known estimator ...  Read More

Predicting the Brexit Outcome Using Singular Spectrum Analysis

Rahim Mahmoudvand; Paulo Canas Rodrigues

Volume 1, Issue 1 , December 2022, , Pages 11-19

https://doi.org/10.22054/jcsm.2018.33508.1006

Abstract
  In a referendum conducted in the United Kingdom (UK) on June 23, 2016, $51.6\\%$ of the participants voted to leave the European Union (EU). The outcome of this referendum had major policy and financial impact for both UK and EU, and was seen as a surprise because the predictions consistently indicate ...  Read More

Differenced-Based Double Shrinking in Partial Linear Models

Mina Norouzirad; Mohammad Arashi; Mahdi Roozbeh

Volume 1, Issue 1 , December 2022, , Pages 21-32

https://doi.org/10.22054/jcsm.2018.33896.1008

Abstract
  Partial linear model is very flexible when the relation between the covariates and responses, either parametric and nonparametric. However, estimation of the regression coefficients is challenging since one must also estimate the nonparametric component simultaneously. As a remedy, the differencing approach, ...  Read More

Statistical Computing
Statistical Topology Using the Nonparametric Density Estimation and Bootstrap Algorithm

Soroush Pakniat

Volume 1, Issue 1 , December 2022, , Pages 33-44

https://doi.org/10.22054/jcsm.2018.9248

Abstract
  This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables ...  Read More

Computational Statistics
Economic Statistical Design of a Three-Level Control Chart with VSI Scheme

Reza Pourtaheri

Volume 1, Issue 1 , December 2022, , Pages 45-58

https://doi.org/10.22054/jcsm.2018.30016.1005

Abstract
  Traditionally, the statistical quality control techniques utilize either an attributes or variables product quality measure. Recently, some methods such as three-level control chart have been developed for monitoring multi attribute processes. Control chart usually has three design parameters: the sample ...  Read More

Inference on Pr(X > Y ) Based on Record Values From the Power Hazard Rate Distribution

Bahman Tarvirdizade; Nader Nematollahi

Volume 1, Issue 1 , December 2022, , Pages 59-76

https://doi.org/10.22054/jcsm.2018.9250

Abstract
  In this article, we consider the problem of estimating the stress-strength reliability $Pr (X > Y)$ based on upper record values when $X$ and $Y$ are two independent but not identically distributed random variables from the power hazard rate distribution with common scale parameter $k$. When the parameter ...  Read More

Statistical Simulation
Assessment Estimation Modeling of the Midpoint Coefficient for Imprecise Data

farzad eskandari

Volume 1, Issue 1 , December 2022, , Pages 77-97

https://doi.org/10.22054/jcsm.2018.36479.1011

Abstract
  Imprecise measurement tools produce imprecise data. Interval-valued data is usually used to deal with such imprecision. So interval-valued variables are used in estimation methods. They have recently been modeled by linear regression models. If response variable has any statistical distributions, interval-valued ...  Read More

Statistical Computing
Minimum Loss Design of X Control Chart for Correlated Data Under Weibull In-Control Times with Multiple Assignable Causes

mohammad hossein naderi; Mohammad Bameni Moghadam; asghar Seif

Volume 1, Issue 1 , December 2022, , Pages 99-127

https://doi.org/10.22054/jcsm.2018.36532.1014

Abstract
  A proper method of monitoring a stochastic system is to use the control charts of statisticalprocess control in which a drift in characteristics of output may be due to one or several assignable causes. In the establishment of X charts in statistical process control, an assumption is made that there ...  Read More

Bayesian Computation Statistics
Bayesian Nonparametric Bivariate Meta Analysis

Ehsan Ormoz

Volume 1, Issue 1 , December 2022, , Pages 129-141

https://doi.org/10.22054/jcsm.2018.36484.1013

Abstract
  In the meta-analysis of clinical trials, usually the data of each trail summarized by one or more outcome measure estimates which reported along with their standard errors. In the case that summary data are multi-dimensional, usually, the data analysis will be performed in the form of a number of separated ...  Read More

Nonparametric Wavelet Quantile Density Estimations Based on Biased Data

Esmaeil Shirazi

Volume 1, Issue 1 , December 2022, , Pages 143-158

https://doi.org/10.22054/jcsm.2018.34089.1009

Abstract
  Estimation of a quantile density function from biased data is a frequent problem in industrial life testingexperiments and medical studies. The estimation of a quantile density function in the biased nonparametric regression model is inves-tigated. We propose and develop a new wavelet-based methodology ...  Read More

Semiparametric Ridge Regression for Longitudinal Data

mozhgan taavoni

Volume 1, Issue 1 , December 2022, , Pages 159-170

https://doi.org/10.22054/jcsm.2019.36950.1015

Abstract
  This paper considers an extension of the linear mixed model, called semiparametric mixed effects model, for longitudinal data, when multicollinearity is present. To overcome this problem, a new mixed ridge estimator is proposed while the nonparametric function in the semiparametric model is approximated ...  Read More

Bayesian Computation Statistics
Bayesian Variable Selection in Regression Models Using the Laplace Approximation

sima naghizadeh

Volume 1, Issue 1 , December 2022, , Pages 171-188

https://doi.org/10.22054/jcsm.2019.43908.1018

Abstract
  The Bayesian variable selection analysis is widely used as a new methodology in air quality control trials and generalized linear models. One of the important and, of course, controversial topics in this area is selection of prior distribution of unknown model parameters. The aim of this study is presenting ...  Read More

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

The impact of audit quality on reducing collateral facilities and the role of major shareholders in listed companies of Tehran exchange market

Mahsa Ghajarbeigi; Hamid Reza Vakely fard; Ramzanali Roeayi

Volume 2, Issue 1 , December 2023, , Pages 1-19

https://doi.org/10.22054/jcsm.2022.70725.1035

Abstract
  The purpose of this paper was to investigate the impact of audit quality on the reduction of collateral facilities, taking into account the role of major shareholders in companies listed on the Tehran Stock Exchange during the period 2017 to 2022. Considering the research conditions, 179 companies were ...  Read More

Bayesian Computation Statistics
Bayesian nonparametric estimation for big data classification

Rashin Nimaei; Farzad Eskandari

Volume 2, Issue 2 , June 2024, , Pages 1-14

https://doi.org/10.22054/jdsm.2025.82037.1054

Abstract
  ‎The recent advancements in technology have faced an increase in the growth rate of data‎.‎According to the amount of data generated‎, ‎ensuring effective analysis using traditional approaches becomes very complicated‎.‎One of the methods of managing and analyzing big data ...  Read More

Bayesian Computation Statistics
Bayesian Semiparametric Meta-Regression Model

Ehsan Ormoz; Farzad Eskandari

Volume 2, Issue 2 , June 2024, , Pages 15-34

https://doi.org/10.22054/jdsm.2025.82599.1057

Abstract
  This paper introduces a novel semiparametric Bayesian approach for bivariate meta-regression. The method extends traditional binomial models to trinomial distributions, accounting for positive, neutral, and negative treatment effects. Using a conditional Dirichlet process, we develop a model to compare ...  Read More

A New Approach Based on Business Intelligence and Bayesian Network for Analysis of Corporate Accounting Systems

azar ghyasi; hanieh rashidi

Volume 2, Issue 1 , December 2023, , Pages 21-37

https://doi.org/10.22054/jcsm.2022.69949.1033

Abstract
  Due to the inherent complexity and increasing competition, today's business environment requires new approaches in organizing and managing. One of the new approaches is business intelligence, which is the most critical technology to help manage and deliver smart services, especially business reporting. ...  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

Machine Learning
Multi-Objective Interaction-Enhanced Feature Selection for Streaming Multi-Label Data

Sahar Abbasi; Radmin Sadeghian; Maryam Hamedi

Volume 2, Issue 2 , June 2024, , Pages 35-70

https://doi.org/10.22054/jdsm.2024.80654.1049

Abstract
  Multi-label classification assigns multiple labels to each instance, crucial for tasks like cancer detection in images and text categorization. However, machine learning methods often struggle with the complexity of real-life datasets. To improve efficiency, researchers have developed feature selection ...  Read More

Machine Learning
INTELLIGENT MODELING OF PERSIAN VERNACULAR ARCHITECTURE BASED ON THE FUZZY DELPHI METHOD (FDM)

Mostafa Azghandi; Mahdi Yaghoobi; Elham Fariborzi

Volume 2, Issue 1 , December 2023, , Pages 39-59

https://doi.org/10.22054/jdsm.2024.78060.1042

Abstract
  By focusing on the fuzzy Delphi technique (FDM), the current research introduces a novel approach to modeling Persian vernacular architecture. Fuzzy Delphi is a more advanced version of the Delphi Method, which utilizes triangulation statistics to determine the distance between the levels of consensus ...  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

Statistical Simulation
Automatic evaluation of record linkage methods in the expert system of producing statistical registers: string metric approach

Vadood keramati; Ramin Sadeghian; Maryam Hamedi; Ashkan Shabbak

Volume 2, Issue 1 , December 2023, , Pages 61-77

https://doi.org/10.22054/jdsm.2024.76812.1039

Abstract
  Record linkage is a tool used to gather information and data from different sources. It is used in activities related to government, such as e-government and the production of register-based data. This method compares the strings in the databases and there are different methods for record linkage, such ...  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

Machine Learning
Enhanced Decision Support System for Breast Cancer Diagnosis with Weighted Ensemble Learning Methods

Mohammad Zahaby; Iman Makhdoom

Volume 2, Issue 2 , June 2024, , Pages 71-102

https://doi.org/10.22054/jdsm.2025.82414.1055

Abstract
  Breast cancer (BC) is one of the leading causes of death in women worldwide. Early diagnosis of this disease can save many women’s lives. The Breast Imaging Reporting and Data System (BIRADS) is a standard method developed by the American College of Radiology (ACR). However, physicians have had ...  Read More

Computational Statistics
The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran

Manijeh Mahmoodi; Mohammad Reza Salehi Rad; Farzad Eskandari

Volume 2, Issue 1 , December 2023, , Pages 79-93

https://doi.org/10.22054/jdsm.2024.78857.1044

Abstract
  AbstractThe novel corona virus (covid-19) spread quickly from person to another and one of the basic aspects of the country management has been to prevent the spread of this disease. So the prediction of its expansion is very important. In such matters, the estimation of new cases and deaths in covid-19 ...  Read More