• Ph.D. (1997)


    Department of Statistics, Leeds University, Leeds, England

  • M.Sc. (1986)


    Department of Statistics, Tarbiat Modares University, Tehran, Iran

  • M.Sc. (1980)


    Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran

  • Spatial and Spatio-Temporal Statistics
  • Spatial Survival Data Analysis
  • Spatial Data Sciences
  • Bayesian Statistical Inference
  • Official Statistics
  • Research field:




Strong support professional with a Doctor of Philosophy (Ph.D.) focused on Spatial Statistics from the University of Leeds in the UK., Has experience in education, research and execution in higher education. Skilled in Statistical Inference, Empirical Bayes, Statistical Modeling, Spatial and Spatio-Temporal Data Analysis, Statistical Modeling and Spatial Data Sciences.


Curriculum Vitae (CV)

Generalized Skew Laplace Random Fields: Bayesian Spatial Prediction for Skew and Heavy Tailed Data

Mohammad Mehdi Saber, Alireza Nematollahi, Mohsen Mohammadzadeh
Journal PaperJournal of Statistical Theory and Applications , 2021 January , {Pages }


Earlier works on spatial prediction issue often assume that the spatial data are realization of Gaussian random field. However, this assumption is not applicable to the skewed and kurtosis distributed data. The closed skew normal distribution has been used in these circumstances. As another alternative, we apply generalized skew Laplace distributions for defining a skew and heavy tailed random field for Bayesian prediction. Simulation study and a real problem are then applied to evaluate the performance of this model.

Spatial Varying Coefficient Regression Model For Relative Risk Factors of Esophageal Cancer Patients

Kimia Kazemi, Mohsen Mohammadzadeh
Journal PaperAndish-ey Amari , Volume 25 , Issue 2, 2021 January , {Pages 103-112 }


In conventional methods for spatial survival data modeling, it is often assumed that the coefficients of explanatory variables in different regions have a constant effect on survival time. Usually, the spatial correlation of data through a random effect is also included in the model. But in many practical issues, the factors affecting survival time do not have the same effects in different regions. In this paper, we consider the spatial effects of factors affecting survival time are not the same in the different areas.For this purpose, spatial regression models and spatial varying coefficient models are introduced. Next, the Bayesian estimates of their parameters are presented. Three models of classical regression, spatial regression and sp

Bayesian analysis of generalized linear mixed models with spatial correlated and unrestricted skew normal errors

Mohadeseh Alsadat Farzammehr, Mohsen Mohammadzadeh, Mohammad Reza Zadkarami, Geoffrey J McLachlan
Journal PaperCommunications in Statistics-Theory and Methods , 2021 March 4, {Pages 22-Jan }


Existing studies on spatial linear mixed models typically assume a normal distribution for the random error components. However, such an assumption may not be appropriate in many applications. This work relaxes the normality assumption of a generalized linear mixed model with spatial correlated by using an unrestricted multivariate skew-normal distribution, which includes the normal distribution as a special case. For parameter estimation, a Bayesian inference algorithm is developed. A simulation study and the analysis of a real data set of cigarette consumption observed between 1963 and 1992 located in 46 states of the US are conducted to compare the proposed skew normal spatial mixed model with the normal spatial mixed model.

Spatio-Temporal Prediction of a Nonstationary and Nonseparable Random Fields with Tucker Decomposition of Covariance Tensor

M Mohammadzadeh, S Saadati
Journal Paper , , {Pages }


A multi-objective sampling design for spatial prediction problem

E Lotfian, M Mohammadzadeh
Journal Paper , , {Pages }


Extended Generalized Skew Laplace Random Field: Spatial Autoregressive and Moving Average Model for Skew and Heavy Tailed Data

MM Saber, A Nematollahi, M Mohammadzadeh
Journal Paper , , {Pages }


Bayesian prediction of spatial data with non-ignorable missingness

Samira Zahmatkesh, Mohsen Mohammadzadeh
Journal PaperStatistical Papers , 2020 June 10, {Pages 22-Jan }


In spatial data, especially in geostatistics data where measurements are often provided by satellite scanning, some parts of data may get missed. Due to spatial dependence in the data, these missing values probably are caused by some latent spatial random fields. In this case, ignoring missingness is not logical and may lead to invalid inferences. Thus incorporating the missingness process model into the inferences could improve the results. There are several approaches to take into account the non-ignorable missingness, one of them is the shared parameter model method. In this paper, we extend it for spatial data so that we will have a joint spatial Bayesian shared parameter model. Then the missingness process will be jointly modeled with

Modeling of Spatio-Temporal Data with Non-Ignorable Missing

Mohsen Mohammadzadeh, Samira Zahmatkesh
Journal PaperJournal of Advanced Mathematical Modeling , Volume 10 , Issue 1, 2020 May 21, {Pages 39-61 }


Often, due to conditions under which measurements are made, spatio-temporal data contain missing values. Missing data in spatial or temporal vicinity may include useful information. Using this information, we can provide more accurate results, so missing data should be carefully examined. By modeling the missing process and spatio-temporal measurement process jointly, some lost information could be recovered. In this paper, we implement joint modeling in a Bayesian framework using the "shared parameter model" technique, so that the bad effects of missing values will be moderated. Also, we will associate these two processes via a latent spatio-temporal random field. To estimate the model parameters and for predictions, the Bayesian method IN

Trivariate non‐Gaussian copulas to analyze the spatial behavior of rat sightings

Carlos Ayyad, Jorge Mateu, Mohammad Omidi, Ibon Tamayo‐Uria, Mohsen Mohammadzadeh
Journal PaperStatistica Neerlandica , Volume 73 , Issue 2, 2019 May , {Pages 256-273 }


The brown rat lives with man in a wide variety of environmental contexts and adversely affects public health by transmission of diseases, bites, and allergies. Understanding behavioral and spatial correlation aspects of pest species can contribute to their effective management and control. Rat sightings can be described by spatial coordinates in a particular region of interest defining a spatial point pattern. In this paper, we investigate the spatial structure of rat sightings in the Latina district of Madrid (Spain) and its relation to a number of distance‐based covariates that relate to the proliferation of rats. Given a number of locations, biologically considered as attractor points, the spatial dependence is modeled by distance‐ba

Bayesian Analysis of Spatial Survival Model with Non-Gaussian Random Effect

K Motarjem, M Mohammadzadeh, A Abyar
Journal PaperJournal of Mathematical Sciences , Volume 237 , Issue 5, 2019 March 21, {Pages 692-701 }


One of the most popular models in survival analysis is the Cox proportional hazards model. This model has been widely used because of its simplicity. Despite its simplicity, the basic problem of the Cox model is its inability to enter unknown risk factors into the model. Some risk factors may affect the survival of a trial unit, but due to time and cost constraints, there is no possibility to measure all of these factors in the form of explanatory variables in the model. In many cases, measuring risk factors is not possible. For entering unknown risk factors into the model, a positive random variable, representative of unknown risk factors, is multiplied in the model. Then a new class of survival models, namely frailty models, is introduced

Evaluation of soil pollution sources using multivariate analysis combined with geostatistical methods in Zanjan Basin, Iran

Mehdi Boroumandi, Mashalah Khamechiyan, Mohammad Reza Nikoudel, Mohsen Mohammadzadeh
Journal PaperGeopersia , 2019 February 23, {Pages }


The increase of heavy metals concentration in soils is potentially threatening the environment and human health. In this paper, multivariate analysis methods such as Positive Matrix Factorization (PMF), Principal Component Analysis (PCA) and Cluster Analysis (CA) combined with geostatistical method were employed to identify the potential sources of soil pollution. A collection of 103 samples were obtained from surface soils of different types of lithology and landuse in Zanjan Basin, Iran. The concentration of As, Bi, Cd, Co, Cr, Cu, Pb, Fe, Mo, Ni, Zn, Se and Hg beside of physical and chemical properties were measured. The results showed a strong effect of anthropogenic sources on the enrichment of heavy metals especially, Zn, Pb, Cd, As a

Analysis of Spatial Data with Non-Ignorable Missingnesss

Mohsen Mohammadzadeh, Samira Zahmatkesh
Journal Paperon Spatial Statistics and Its Applications , 2019 October 23, {Pages 88 }


Many researchers are dealing with spatially dependent data in various sciences such as meteorology, ecology, geology and epidemiology in which there is often a notable amount of missing values. Because spatial data are often collected in nonlaboratory environments, some of the factors affecting measurement, such as environmental and atmospheric conditions, sample units locations, or the time of collecting observations, make missing data inevitable. For spatial data, due to dependency between observations, missing values that are located at the spatial or temporal neighbourhoods of the observations can include useful information that the retrieval of this lost data can increase the accuracy of data analysis. In this paper, the joint modeling

On Spatial Skew-Gaussian Process and Its Applications in Survival Analysis

Kiomars Motarjem, Mohsen Mohammadzadeh
Journal Paperon Spatial Statistics and Its Applications , 2019 October 23, {Pages 109 }


Considering a Gaussian random field for the spatial random effects in survival analysis sometimes may not correspond to reality. In this paper, by considering a Spatial Skew Gaussian process for random effects we propose a new class of spatial survival models. In a simulation study, we have shown that the deviation from Gaussian assumption about the random effects have an undesirable effect on the estimation of model parameters, whereas the use of spatial skew Gaussian random effects provides more accurate models.

The Mediator Role of Occupational Self-Efficacy in the Relationship Be-tween Professional Development and Job Commitment and Satisfaction Among Sports and the Youth Department?…

Mohsen Shir Mohammadzadeh, Abolfazl Ghasemzadeh Alishahi, Mehdi Kazemzadeh Beytali
Journal Paper , 2018 July 7, {Pages }


Background: The aim of present study was to investigate the mediator role of occupational self-efficacy in the relationship between professional development and job commitment and satisfaction among staff of sports and the youth department of east Azerbaijan province in 2016-2017.Methods: This descriptive correlation study is a structural equation model. The statistical population included 322 employees of Sports and the Youth Department of East Azerbaijan province. 203 of them were selected using stratified random sam-pling; which was used to determine the sample size from the Morgan table. For data collection, standard questionnaires were used. Data analysis was performed using descriptive indexes and structural equation modeling method.R

Association of Serotonin Transporter Gene Polymorphism with Recurrent Aphthous Stomatitis

Shamsolmolouk Najafi, Mahsa Mohammadzadeh, Amirabbas Zahedi, Mansour Heidari, Nima Rezaei
Journal PaperAvicenna journal of medical biotechnology , Volume 10 , Issue 1, 2018 January , {Pages 56 }


Background: Recurrent Aphthous Stomatitis (RAS) is one of the most common diseases of the oral cavity all over the world (5–66%). RAS has a multifactorial etiology, while psychological factors such as stress and anger play a role in its manifestation. The serotonergic mechanisms particularly the serotonin-transporter gene (5-HTT) may affect the risk of psychological alterations and stress response. The aim of the present study was to evaluate the polymorphism of the promoter region of 5-HTT (5-HTTLPR) in the patients with RAS, compared to that in the control subjects. Methods: In this case-control study, 100 patients with RAS and 100 healthy subjects were enrolled. PCR was performed on DNA of the samples, using a pair of primers capable o

The Shear Loading Capacity and Behavior of Horizontally Curved Steel I-girder Bridges, and the Imperfection Effect

MM Alinia, M Mohammadzadeh
Journal Paper , Volume 49 , Issue 400130, 2018 January 1, {Pages 733-744 }


In this study, horizontally curved steel I-girder bridges having various radii of curvatures in practical dimensions, and designed via the AASHTO standards are modeled and analyzed via the finite element software ABAQUS. The aim of these material-geometric non-linear analyses are to characterize the shear behavior, the shear failure mechanism and the shear resistance of steel I-girders in the complete bridge systems and in their equivalent single girders. Results demonstrated that the shear behavior, the ultimate shear resistance, the shear buckling resistance of single-girders and bridge system are similar; whereas the initial stiffness of the two approaches differ. Furthermore, the equivalent single-girders are incapable of predicting the

Autosomal dominant deficiency of the interleukin-17F in recurrent aphthous stomatitis: Possible novel mutation in a new entity

Alireza Zare Bidoki, Ahmad Massoud, Shamsolmoulouk Najafi, Mahsa Mohammadzadeh, Nima Rezaei
Journal PaperGene , Volume 654 , 2018 May 15, {Pages 64-68 }


Recurrent Aphthous Stomatitis (RAS) is a common oral inflammatory disease with unknown pathogenesis. Although the immune system alterations could be involved in predisposition of individuals to oral candidiasis, precise etiologies of RAS have not been understood yet. A recent study showed that autosomal dominant IL17F deficiency could cause chronic mucocutaneous candidiasis. Considering the inflammatory nature of interleukin (IL)-17F and RAS, this study was performed to check any disease-associated mutation in a number of patients with RAS. Sixty-two Iranian individuals with RAS were investigated in this study. After DNA extraction using a phenol-chloroform method from the whole blood, amplification was accomplished by polymerase chain reac

Generalized Asymmetric Laplace random fields: Existence and Application.

MM Saber, AR Nematollahi, M Mohammadzadeh
Journal PaperJournal of Data Science , Volume 16 , Issue 1, 2018 January 1, {Pages }


Some specific random fields have been studied by many researchers whose finite-dimensional marginal distributions are multivariate closed skewnormal or multivariate extended skew-t, in time and spatial domains. In this paper, a necessary and sufficient condition is provided for applicability of such random field in spatial interpolation, based on the marginal distributions. Two deficiencies of the random fields generated by some well-known multivariate distributions are pointed out and in contrast, a suitable skew and heavy tailed random field is proposed. The efficiency of the proposed random field is illustrated through the interpolation of a real data.

Emotional health and coping mechanisms among adolescents in Malaysian residential foster care homes: A comparative study with adolescents living with families

Marjan Mohammadzadeh, Esra Tajik, Hamidin Awang, Latiffah Abdul Latiff
Journal PaperAsian journal of psychiatry , Volume 32 , 2018 February 1, {Pages 156-158 }


Adolescents living in residential foster cares and orphanages, in addition to the problems specific to their age, face various problems caused by not having parents leading these young people to have a higher level of daily stress than those who live with their parents (Wanat et al., 2010, Tajik et al., 2017). Findings of the previous study showed that children and adolescents brought up in institutions and residential care homes are three to seven times more likely than non-institutionalized adolescents to be exposed to various emotional and behavioral problems such as aggression, anxiety and depression (Simsek et al., 2007, Fawzy and Fouad, 2010). Malaysia was home to 450,000 orphaned children in 2013, and residential homes are still the

Spatial Interpolation Using Copula for non-Gaussian Mod-eling of Rainfall Data

Mehdi Omidi, Mohsen Mohammadzadeh
Journal PaperJIRSS-JOURNAL OF THE IRANIAN STATISTICAL SOCIETY , Volume 17 , Issue 2, 2018 January 1, {Pages 165-179 }


One of the most useful tools for handling multivariate distributions of dependent variables in terms of their marginal distribution is a copula function. The copula families capture a fair amount of attention due to their applicability and flexibility in describing the non-Gaussian spatial dependent data. The particular properties of the spatial copula are rarely seen in all the known copula families. In the present paper, based on the weighted geometric mean of two Max-id copulas family, the spatial copula function is provided. Afterwards, the proposed copula along with the Bees algorithm is used to explore the spatial dependency and to interpolate the rainfall data in Iran’s Khuzestan province.

Current Teaching

  • MS.c.

    Spatial Statistics I

  • MS.c.

    Spatial-Temporal Data Analysis

Teaching History

    Data not found
  • 2021
    Poursaeed, Roya
    Predicting the Survival of Patients with Glioblastoma Cancer by Clinical, Radiomic and Multi-Omic Data Analysis Using Deep Learning
  • 2021
    Peyvandi, Fatemeh
    Data not found
  • Member of the Basic Sciences Commission of the Science, Research and Technology High Council
  • Member of Audit Board of Shahid Beheshty University.
  • Member of the Specialized Group for Planning and Developing of Statistics, Ministry of Science, Research and Technology
  • Member of the Supervisory and Evaluation Council, Tarbiat Modares Univers
  • Member of the Expert Commission of Audit Board of the Statistical Research and Training Center
  • Editor in Chief of the Journal of Statistical Sciences
  • Editor in Chief of the Iranian Journal of Official Statistics Studies
  • Editorial Board of the Journal of Mathematical Sciences and Informatics
  • Deputy of Support and Human Resources of Tarbiat Modares University
  • Member of Prosperity Fund of Tarbiat Modares University
  • Member of Audit Board of Tarbiat Modares University
  • Member of the Expert Commission of Audit Board of Tarbiat Modares University
  • Head of Department of Statistic, Tarbiat Modares University
  • Editorial Board of the Journal of Sciences, Islamic Republic of Iran.
  • Member of Audit Board of Shahid Beheshty University
  • Deputy for Monitoring and Assessment, University of Applied Science and Technology



    no record found