Thanoon Y Thanoon

• PhD in Statistics. University Technology Malaysia
• Professor at Northern Technical University

The current study sought to determine the quality of management information systems & their contribution to customer orientation at two private universities located in Dohuk Governorate: Cihan & Nawroz. From this point of view, the study problem was identified by the following question: Does the quality of management information systems contribute...

محاضرة عن فن اعداد الاسئلة الامتحانية

Seminar on Bayesian CFA

Workshop on SEM

The purpose of this research is to compare between quadratic and logistic discrimination function, also to identify the best method in discrimination which helps us to classify the data correctly. A several stages are starting from stratified sampling; classification errors and error rate if the pre-probability is equal and unequal by containing a...

This paper reports the use of a numerical solution of nanofluid flow. The boundary layer flow over a stretching sheet in combination of two nanofluids models is studied. The partial differential equation that governs this model was transformed into a nonlinear ordinary differential equation by using similarity variables, and the numerical results w...

The purpose of this paper is to develop a latent variable model with nonlinear covariates and latent variables. Mixed ordered categorical and dichotomous variables and covariates with two different types of thresholds (with equal and unequal spaces) are used in Bayesian multi-sample nonlinear latent variable models and the Gibbs sampling method is...

In this paper, we develop generalized latent variable models with non-linear variable and covariate. Dichotomous variables and covariates are used in this research, and the Gibbs sampling method (Markov chain Monte-Carlo simulation) is applied for estimation. The deviance information Criterion (DIC) is used as a model comparison statistics. Truncat...

تعليمات الترقية العلمية

In this paper, Bayesian analysis is used in nonlinear structural equation models with two population of data and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of ordered categorical data in Bayesian multiple group SEMs and c...

The purpose of this paper is to describe the mixed variables (ordered categorical and dichotomous) in Bayesian structural equation models. Markov chain Monte Carlo simulation (MCMC) via Gibbs sampling method is applied for estimation the parameters. Statistical analyses, which include parameters estimation, standard error, higest posterior density...

In this paper, ordered categorical variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical analyses, which involve estimation of parameters and their standard deviations for testing the selected model, are discussed. The propose...

In this paper, ordered categorical variables are used to compare between linear and nonlinear interactions of fixed covariate and latent variables Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) is used to handle the probl...

In multiple correspondence analysis, whenever the number of variables exceeds the number of observations, row matrix should be used, but if the number of variables is less than the number of observations column matrix is the suitable procedure to follow. One of the following matrices (rows, columns) leads to loss of information that can be found by...

In this paper, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analysis for testing the selected model, are disc...

This paper is designed to give a complete overview of the literature that is available, as it relates to application of the Bayesian analysis model to investigate multiple group nonlinear structural equation models, also known as SEMs, including those having ordered categorical, dichotomous and categorical-dichotomous mixed variables. It will also...

In this paper, mixed ordered categorical and dichotomous variables were used in Bayesian multi-sample nonlinear structural equation models and the Gibbs sampling method was applied to compare models and estimates. Hidden continuous normal distribution (censored normal distribution) was used to solve the problem of mixed ordered categorical and dich...

Canonical correlation analysis is used to study the relationship between two groups of variables (dependent and independent). Since each group represents the linear combination to a number of variables, canonical correlation analysis measures the relationship between these variables that maximally correlate with linear combinations of another subse...

In this paper, ordered categorical and dichotomous data are used in generalized nonlinear canonical correlation analysis to study the relationship between two or more sets of variables. Statistical analyses involving generalized nonlinear canonical correlation analysis, component loadings, and object scores are discussed in this paper. The proposed...

In this paper, continuous and dichotomous variables are used in multiple factor analysis method. When all variables within the same group are continuous, we use principal component analysis method in factor analysis, if all variables within the same group are dichotomous we use multiple correspondence analysis method in factor analysis. Statistical...

Factor scores is one of the results of the factor analysis which consist of (n*m) matrix , where n is the number of observations and m represent the number of variables , used cluster analysis and discriminant analysis methods in classification based on factor scores results and application this study on (30) observations taking from technical inst...

Using Bayesian inference in factor analysis is to estimate parameters of the model (,F ) , Where  represents the factor loadings matrix, F represents the factor scores matrix, for that, selected variables of interest relatively through interpretation are the results of Bayesian estimator for factor loadings matrix and application on data taken fr...

In this research we use path analysis to study the variables affecting the scientific level of institute students. Data were from the Technical Institute of Nineveh Examination Committee for students of the first stage Department of Financial and Banking for the academic year 2008-2009 which contains eight independents variables represent study mat...

Use factor analysis to forecasting the time-series by converting the time series into factor analysis scores by utilizing the method of Box-Jenkins for time series analysis based on a of variance-covariance matrix and application on two variables (two series) : (Y t) represents a series of monthly rains for Mosul station and (X t), which represents...

Expectation maximization algorithm (EM) is used to create estimator with the same qualities of maximum likelihood estimator by taking into consideration the existence of two types of data, data viewing (observe data) and hidden data (missing data). Maximum likelihood method in factor analysis is applied in this research to estimate the parameters o...

Expectation maximization algorithm (EM) is used to create estimator with the same qualities of maximum likelihood estimator by taking into consideration the existence of two types of data, data viewing (observe data) and hidden data (missing data). Maximum likelihood method in factor analysis is applied in this research to estimate the parameters o...

Cluster analysis is divided into two methods (Hierarchical agglomerative method) and (partitioning method) and in this research it is used (complete linkage method) which is considered as one of the important methods of hierarchical agglomerative method and most common applied to data taken from the college of sport education in Mosul university ,t...

Measures of nine variables affect the births of the premature babies have been taken. And also the principal axis method was used then the factor analysis on the studied variables data to specify the importance of these variables to births of the premature babies. As well as , "Varimax" method was used to rotate the axis to get an easier and more s...

In factor analysis, whenever the number of variables (m) is less than the number of the experimental units (n). The procedure of R-mode should be applied, if (m) exceed (n) the Q-mode is the suitable procedure to follow. A shortcut transformation between the results of the two procedures was established in any analytical step. Some of the results a...

Used regression analysis Procedures ( Forward selection Procedure, Backward Elimination Procedure, Stepwise Regression Procedure) for selection variables have significant effect and applying on data for patient injured acute leukemia, after then finding discriminate analysis depending on significant variables which appear significant effect at calc...