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

  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

  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

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

  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

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

  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

  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

  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

  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

  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

  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

  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