# A. R. NematollahiShiraz University · Department of Statistics

A. R. Nematollahi

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74

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Introduction

**Skills and Expertise**

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June 2000 - present

## Publications

Publications (74)

Microtubule affinity-regulating kinase 4 (MARK4) is a Ser/Thr protein kinase, best known for its role in phosphorylating microtubule associated proteins, causing their detachment from microtubules. In the current study, the non-phosphorylated conformation of the activation loop was modeled in a structure representing the enzymatically inactive form...

The classical autoregressive type models are widely used in time series modelling. Recently, a class of models known as generalized autoregressive, recognized by an additional parameter, has been proposed in order to reveal some hidden features which cannot be characterized by the standard autoregressive models. In this paper, the generalized autor...

Papaver pseudo-orientale Medw is a hexaploid plant with 42 chromosomes found in the northwest of Iran and throughout eastern Turkey. In this study, three populations of P. pseudo-orientale species were collected from three habitats (Solik, Golshikhan, and Qotur) in West Azerbaijan province, and their morphological characteristics as well as amino a...

This article studies long-term, short-term volatility and co-volatility in stock markets by introducing modelling strategies to the multivariate data analysis that deal with serially correlated innovations and cross-section dependence. In particular, it presents an innovative mixed-effects model through a GARCH process, allowing for heterogeneity e...

We consider here a periodic autoregressive model with scale mixtures of skew-normal innovations. The class of scale mixtures of skew-normal distributions is a general and quite flexible class of error distributions, which is often used for statistical procedures of analyzing symmetrical and asymmetrical data. Our aim is to compare some well-known p...

In this paper, a web-based shiny application called the ‘PAR(1) Model Analysis’— that allows the modelling, estimation and prediction of a periodic autoregressive time series with scale mixtures of skew-normal innovations, a general and quite flexible class of error distributions—is presented. The class of scale mixtures of skew-normal distribution...

A vector autoregressive model of order one with multivariate generalized scaled t-distributed innovations is considered here. The object is to estimate the parameters of the proposed model by using the well-known maximum likelihood estimation method. The maximum likelihood estimation method is performed by using the expectation–conditional maximiza...

Suppose that a system is affected by a sequence of shocks that occur randomly over time, and δ1, δ2, η1 and η2 are critical levels such that 0<δ1<δ2 and 0<η1<η2. In this paper, a new mixed δ-shock model is introduced for which the system fails with a probability, say θ1, when the time between two consecutive shocks is lying in [δ1,δ2], and the syst...

In this paper, the life distribution behavior of a generalization of the mixed \(\delta\)-shock models in the multi-state systems is studied. In this model, the k out of interarrival times between two successive shocks with a magnitude less than \(\delta\) have a disaster result on the system which causes a complete failure. In addition to this eve...

In this paper, we propose a new class of continuous distributions with two extra shape parameters called the new type I half logistic-G family of distributions. Some of important properties including ordinary moments, quantiles, moment generating function, mean deviation, moment of residual life, moment of reversed residual life, order statistics a...

Animal models are used commonly for modeling genetic responses. In these models the response variable can be Gaussian or Non-Gaussian, so these models belong to the generalized linear mixed models, where the genetic correlation structure of data is considered through random effects with the normal distribution. But in many applications, it is uncle...

Microtubule affinity-regulating kinase 4 (MARK4) is a Ser/Thr protein kinase, best known for its role in phosphorylating microtubule associated proteins, causing their detachment from microtubules. In the current study, the non-phosphorylated conformation of the activation loop was modeled in a structure representing the enzymatically inactive form...

This paper is concerned with the estimation problem of a periodic autoregressive model with closed skew-normal innovations. The closed skew-normal (CSN) distribution has some useful properties similar to those of the Gaussian distribution. Maximum likelihood (ML), Maximum a posteriori (MAP) and Bayesian approaches are proposed and compared in order...

In this paper, the life behavior of a shock model is studied, when the external shocks occur according to a binomial process whose interarrival times between successive shocks follow a geometric distribution. The system transits into a lower partially working state upon the occurrence of each interarrival time between two successive shocks less tha...

In this article, a longitudinal functional model including both fixed and random effects which depend on measurement periods is considered. A new procedure is presented to estimate the parameters included in the fixed and random effect terms of the model. We put light on the performance of our estimation procedure by two simulation studies and a re...

Simple harmonizable processes, introduced by Soltani and Parvardeh (Theory Probab Appl 50(3):448–462, 2006), form a fairly large class of second order processes that includes stationary processes and periodically correlated processes. The spectral density of a simple process is supported by certain curves in \([0,2\pi )^2\). In this article we proc...

Periodic autoregressive (PAR) models with symmetric innovations are widely used on time series analysis, whereas its asymmetric counterpart inference remains a challenge, because of a number of problems related to the existing computational methods. In this paper, we use an interesting relationship between periodic autoregressive and vector autoreg...

In this paper, we introduce a test statistics to test whether a discrete time periodically correlated model with a given spectral density explains an observed time series. Our testing procedure is based on an application of the asymptotic distribution of the periodogram established in Soltani and Azimmohseni (Stat Plan Inference 137:1236–1242, 2007...

In this article we consider the sequences of sample and popu- lation covariance operators for a sequence of arrays of Hilbertian random elements. Then, under the assumptions that sequences of the covari- ance operators norm are uniformly bounded and the sequences of the principal component scores are uniformly summable, we prove that the convergenc...

This paper is concerned with the likelihood-based inference of vector autoregressive models with multivariate scaled t-distributed innovations by applying the EM-based (ECM and ECME) algorithms. The ECM and ECME algorithms, which are analytically quite simple to use, are applied to find the maximum likelihood estimates of the model parameters and t...

In this paper, we consider an autoregressive model of order one with skew-normal innovations. We propose several methods for estimating the parameters of the model and derive the limiting distributions of the estimators. Then, we study some statistical properties and the regression behavior of the proposed model. Finally, we provide a Monte Carlo s...

We consider the structures of periodically correlated wide-sense Markov (PCWM) processes and their associated multi-dimensional stationary processes. The main result of the paper concerns the structure of multivariate PCWM processes, in terms of multivariate autoregressive and periodic autoregressive processes. But we also correct some results prev...

Three linear prediction methods of a single missing value for a stationary first order multiplicative spatial autoregressive model are proposed based on the quarter observations, observations in the first neighborhood and observations in the nearest neighborhood. Three different types of innovations including Gaussian (symmetric and thin tailed), e...

The estimation problem of epsilon-skew-normal (ESN) distribution parameters is considered within Bayesian approaches. This family of distributions contains the normal distribution, can be used for analyzing the asymmetric and near-normal data. Bayesian estimates under informative and non-informative Jeffreys prior distributions are obtained and per...

We consider estimation of a missing value for a stationary autoregressive process of order one with exponential innovations and compare two methods of estimation of the missing value, with respect to Pitman's measure of closeness (PMC).

This research was aimed to present a new model to determine the areas with higher degradation risk through considering various indicators of land degradation and desertification aspects or criteria, namely, natural, human and trend of degradation. For this purpose, two areas were selected in the north (Sepidan) and south of the province
(Lamerd). T...

In this paper, we provide necessary conditions for a discrete-time symmetric α-stable processes to be linear 2-ple Markov. The aim of this paper is to extend the results given by Adler et al. (1990) to general multiple Markov processes, called linear multiple Markov processes. A necessary and sufficient condition based on the covariation for SαS pr...

In this article, we consider a (k + 1)n-dimensional elliptically contoured random vector (XT1, X2T, …, XTk, ZT)T = (X11, …, X1n, …, Xk1, …, Xkn, Z1, …, Zn)T and derive the distribution of concomitant of multivariate order statistics arising from X1, X2, …, Xk. Specially, we derive a mixture representation for concomitant of bivariate order statisti...

This paper presents a theoretical and empirical study of likelihood inference for the autoregressive models with finite (m-component) mixture of scale mixtures of Gaussian (SMN) innovations. This model involves autoregressive models with single and mixture component of innovations, which frequently used in time series data analysis. An EM-type algo...

Hydrological processes (models or systems) have both deterministic and stochastic components. In the deterministic models, the state of the systems in time (or space) can be exactly predicted, but in the stochastic models, some random elements are involved. With stochastic analysis, it is possible to calculate time response (delay time) of hydrolog...

Simple harmonizable processes (SHP) introduced by Soltani and Parvardeh (2006) are a large class of nonstationary processes which includes stationary and periodically correlated (PC) processes. Detection and estimation of SHP structure are important problems when dealing with nonstationary data. In this paper, we study the spectral properties of si...

This paper considers the modified exponential- geometric distribution, a new three-parameter lifetime distribution with decreasing or increasing failure rate. Various properties of the proposed distribution are discussed. The estimation of the parameters attained by the EM algorithm and their asymptotic variances and covariances are obtained. A sim...

Applied statistical decision theory has wide applications in decision-making fields of studies, such as economic, business management and industrial managements. In this work, following Pratt et al.’s [Introduction to statistical decision theory. 3rd ed. Cambridge, MA: The MIT Press; 2001] approach, we provide theoretical and practical formulations...

In this paper we introduce a new generalization of skew-t distributions which contains the standard skew-t distribution, as a special case. This new class of distributions is an adequate model for modeling some data set rather than to the standard skew-t distributions. This kind of distributions can be represented as a scale-shape mixture of the ex...

In this paper, we show that the derivation of Lemma 3 of Das and Dey (2010) needs to be corrected by using a logical transformation, instead of the ad-hoc transformation which is partially motivated by its univariate equivalent transformation. The correct derivation is presented by two approaches.

Recently, the strong consistency and asymptotic distribution for the maximum consecutive pairwise likelihood estimators (MCPLE) have been established in the linear time series models. In this paper, the weak convergence of the maximum weighted pairwise likelihood estimator (MWPLE) of the parameters of the AR(1) models is established by using the co...

This article applies the EM-based (ECM and ECME) algorithms to find the maximum likelihood estimates of model parameters in general AR models with independent scaled t-distributed innovations whenever the degrees of freedom are unknown. The ECME, sharing advantages with both EM and Newton–Raphson algorithms, is an extension of ECM, which itself is...

Background:
Elimination of suicide attempts is impossible, but they can be reduced dramatically by an organized planning. The present study aimed to survey the suicide trends in Fars province (Iran), during 2004-2009 to better understand the prevalence and status of suicide.
Methods:
This survey was a cross-sectional study. The demographic data...

This article considers the two-piece normal-Laplace (TPNL) distribution, a split skew distribution consisting of a normal part, and a Laplace part. The distribution is indexed by three parameters, representing location, scale, and shape. As illustrated with several examples, the TPNL family of distributions provides a useful alternative to other fa...

The use of weighted pairwise likelihood instead of the full likelihood in estimating the parameters of the multivariate AR(1) is investigated. A closed formula for typical elements of the Godambe information (sandwich information) is presented. Some efficiency calculations are also given to discuss the feasibility and computational advantages of th...

This paper deals with a direct derivation of Fisher's information matrix for bivariate Bessel distribution of type I. Some tools for the numerical computation and some tabulations of the Fisher's information matrix are provided.

The most important problem in data modeling using the AR model is the order selection. Some AR order selection criteria estimate the prediction error and choose the order that minimizes this estimated prediction error. All of these criteria use the same formula for estimating the prediction error from the residual variance for all AR models. Howeve...

This paper is concerned with the change point analysis in a general class of distributions. The quasi-Bayes and likelihood ratio test procedures are considered to test the null hypothesis of no change point. Exact and asymptotic behaviors of the two test statistics are derived. To compare the performances of two test procedures, numerical significa...

In this paper, a parallel system consisting of a finite number of identical components with independent lifetimes having a common distribution function is considered, when the failure time of the system is restricted to a finite interval (double regularly checking). Under these conditions, the mean past lifetime (MPL) of the system is presented and...

Industrial and agricultural developments cause decreasing groundwater level in the world and Iran also. This tends to drying of water wells, decrease in river flow, lowering of water quality, increase of pumping costs, ground settlements and aquifer death. Shiraz aquifer, area of 270 square kilometer, located in south of Iran. Monthly unit hydrogra...

The final prediction error (FPE) criterion is an asymptotic estimate of the prediction error that is used for autoregressive (AR) model order selection. In this paper, we derive a new theoretical estimate of the prediction error for the same-realization predictions. This estimate is derived for the case that the Least-Squares-Forward (LSF) method (...

Multivariate analysis of statistical methods by using the R and SPSS software has been considered.

This paper is an investigation on the sufficient statistic for the parameters of the vector-valued (multivariate) ARMA models, when a finite sample is available. In the simplest case ARMA(1,1), by using the factorization theorem, we present a sufficient statistic whose dimension depends on the sample size and
this dimension is even larger than the...

Motivated by an application in change point analysis, we derive a closed form for the density function of the sum of n independent, non-identically distributed, uniform random variables.

In the present article, we consider a parallel system consisting of n identical components, such that the lifetimes of components are independent and have a common distribution function F. It is assumed that the total number of failures of the components at time t 1 is m and at time t 2 (t 1 < t 2), all components of the system have failed or the s...

The objective of this paper is to compare estimators which are a function of sample averages (a modification of Zh. Fan’s estimators [J. Stat. Plann. Inference 123, No. 1, 13–40 (2004; Zbl 1097.62043)]) based on different sample sizes for all symmetric stable distributions with exponent α (0<α≤2), according to the Pitman’s measure of closeness crit...

Periodically correlated autoregressive nonstationary processes of finite order are considered. The corresponding Yule-Walker equations are applied to derive the generating functions of the
covariance functions, what are called here the periodic
covariance generating functions. We also provide closed formulas
for the spectral densities by using the...

A useful inequality involving correlations between three random variables with mean zero and finite second moments is presented. The inequality is applied to show that the entries on the main diagonal of the spectral density of a periodically correlated Markov process, as derived in Nematollahi and Soltani [2000. Discrete time periodically correlat...

Autoregressive Gaussian random vectors of order one are introduced, characterized and studied. The characterization in- volves the existence and structural identification of the covariance matrix. Prediction for future values together with necessary and sucient conditions for the stationarity are established. Some ba- sic statistical properties are...

We consider the change point problem in a general class of distributions, and derive a test statistic Tn which reduces to the statistic obtained by Kander and Zacks (1966) for the exponential family. Properties of the test, including its asymptotic distribution, are discussed.

Bivariate time series techniques (in spectral domain) of daily rainfall and water level of piezometers or discharge of springs in karstic aquifers are employed to evaluate the lag times (delay) of aquifers response to rainfall events. The evaluation results show that the physical characteristics of karstic aquifers can be compared with each other b...

Spectral analysis considers the problem of determining (the art of recovering) the spectral content (i.e., the distribution of power over frequency) of a stationary time series from a nite set of measurements, by means of either nonparametric or parametric techniques. This paper introduces the spectral analysis problem, motivates the deenition of p...

Data monitoring is important in the study and analysis of hydrological behaviors of karstic systems. Monitoring shows the various regimes of groundwater flow (laminar or turbulent), depletion, filling, filtration and karstification degree of karst aquifers. In recent years, analyses of these data had considerable advances using stochastic time seri...

We consider the estimation of the spectral density matrix of a periodically
correlated (PC) time series (also known as cyclostationary time series).
We use the well known relation between the spectral density matrix
of a periodically correlated time series and a stationary vector time series
(Gladyshev, 1961). The spectral matrix of the stationary...