About Journal

Iraqi Journal of Statistical Sciences (IQJOSS) is a global, scientific and open access journal. This journal has been published twice a year by the College of Computer Science and Mathematics, University of Mosul, Iraq. The iThenticate is used to prevent plagiarism and to ensure the originality of our submitted manuscripts. A double-blind peer-reviewing system is also used to assure the quality of the publication. The Iraqi Journal of Statistical Sciences was established in 2001 and publishes original research, review papers in the field of Statistical Science, Mathematical and Computers....
Read More ...

Support Vector Regression (SVR) model

Noora Hawa; Salih Muayad

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 1-22
DOI: 10.33899/iqjoss.2022.174327

In this paper, the Support Vector Regression (SVR) model was used, which is defined as an algorithm or a linear model used to predict a specific model. The performance efficiency of the SVR method depends on the selection of its hyperparameters. In this paper, the SVR method was used with the Strawberry Algorithm, which is the proposed algorithm to obtain the best combination of hyperparameters.
The Root Mean Squares Error (RMSE) criterion was used to compare the results obtained using the proposed algorithm with some common algorithms, namely, Grid Search, Genetic Algorithm, Particle swarm optimization, and an annealing algorithm (Simulated Annealing algorithm. Three methods of selection were also used in the strawberry algorithm, roulette wheel selection, elite selection, and roulette wheel with the elite selection method together. The performance of the algorithm was tested through experimental and real data. The results showed that the strawberry algorithm was superior to the common algorithms in choosing the best combination of hyperparameters. The results also showed that the method of choosing the roulette wheel is the best method that gave good results compared to other methods on the experimental and applied sides.

Using Wavelet Shrinkage in the Cox Proportional Hazards Regression model (simulation study)

taha ali; Jwana Rostam Qadir

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 23-45
DOI: 10.33899/iqjoss.2022.174328

The proposed method in this paper dealt with the problem of data contamination in the Cox Proportional Hazards Regression model (CPHRM) by using Wavelet Shrinkage to de-noise data, calculating the discrete wavelet transformation coefficients for wavelets (Symlets and Daubechies), and thresholding methods (Universal, Minimax, and SURE), as well as thresholding rules (Soft and Hard). A software in the MATLAB language built for this propose will compare the proposed and classical method using simulation and real data. All the proposed methods have better efficiency than the classical method in estimating the Cox Proportional hazards model depending on both average of Akaike and Bayesian information criterion.
 Keywords: Cox PH model, Wavelet Shrinkage, thresholding rules.

Comparison of prediction using Matching Pattern and state space models

heyam Abd Al-majeed hayawi; najlaa saad

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 46-59
DOI: 10.33899/iqjoss.2022.174329

Predicting future behavior is one of the important topics in statistical sciences due to the need for it in different areas of life, and most countries rely on their development programs on advanced scientific foundations and methods in order to reach more effective results. This research deals with a comparison of the accuracy of time series prediction using state space models and the matching patterns method of Singh (2001) algorithm by applying to real data, which are economic observations that were previously addressed by the researchers Box and Jenkins (1976). Where the inputs represent the leading indicator and the outputs represent sales, and the importance of this research is represented in Knowing the most accurate method for predicting time series. The MATLAB program has been used to access the results of the research. The most important results of the research are that the state space model is more accurate in forecasting than the matching patterns in the studied data because it has the lowest values ​​of the test criteria of prediction accuracy results.

Spatial Prediction of Real Sulfur Data Using the Ordinary Kriging Technique and Lognormal Kriging

Najla Sedek

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 60-71
DOI: 10.33899/iqjoss.2022.174330

This research deals with the spatial prediction process in order to obtain the optimal prediction when the data are distributed normally. In this paper, we used the ordinary kriging technique and the lognormal kriging after taking the logarithm of the original sulfur data. We used the variogram function in this research to get the best model for the covariance function. The aim of this research is to evaluate the normal kriging and the lognormal kriging and find outliers. The data adopted in this work are from the hydrogeological study of Mosul Governorate/Iraq. Through the results, it was found that the errors in the estimated value are very important for the variance of the estimator, which appears to be very small. As well as through the results that were supported by graphs, we note that the lognormal kriging has more effect than the ordinary Kriging technique under the prediction process, from During the implementation of the error tests which seemed to be very small and which support the predictive values ​​of the spatial sulfur data, the MATLAB programming language was used to obtain the practical results.

Shrinkage estimators in inverse Gaussian regression model: Subject review

Farah Abd ulghani; رفل ادیب الحمدانی

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 72-82
DOI: 10.33899/iqjoss.2022.174331

The presence of the high correlation among predictors in regression modeling has undesirable effects on the regression estimating. There are several available biased methods to overcome this issue. The inverse Gaussian regression model (IGRM) is a special model from the generalized linear models. The IGRM is a well-known model in research application when the response variable under the study is skewed data. Numerous biased estimators for overcoming the multicollinearity in IGRM have been proposed in the literature using different theories. An overview of recent biased methods for IGRM is provided. A comparison among these biased estimators allows us to gain an insight into their performance.

Generalized ratio-cum-product type exponential estimation of the population mean in median ranked set sampling

Rikan .AL_Rahman; Saja Mohammad

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 83-97
DOI: 10.33899/iqjoss.2022.174332

This study presents a proposal to estimate the finite population's mean of the main variable by median ranked set sampling



















 through the generalized ratio-cum-product type exponential estimator. The relative bias

, mean squared error

 and percentage relative efficiencies

of the proposed estimator is obtained to the first degree of approximation. The proposed estimator are more efficient than the usual unbiased estimator, ratio, product type, and other estimators. Finally, the estimators' abilities are evaluated through simulations, showing that the proposed estimator is more efficient than several other estimators.

Identification of Transformation Function Models for OPEC Crude Oil Prices

hashim huseen; najlaa saad

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 98-113
DOI: 10.33899/iqjoss.2022.174333

    The transformation function model is one of the basic concepts in time series as it deals with multivariate time series. As for the design of this model, it depends on the data available in the time series and on other information in the series. Therefore, the representation of the transformation function model depends on the representation of data and the accuracy of the available information. and use this information in modeling. The research aims to identification the transformation function model of the monthly time series of crude oil barrel prices of the Organization of Petroleum Exporting Countries (OPEC) in US dollars as a series of outputs and the price of Brent oil as a series of inputs during the time period from (2005) to (2019). The transformation function model with the order (s,r,d,pn,qn)=(2,2,0,2,3) is the best for representing the data and the mean error criterion was used to know the prediction accuracy of the estimated transformation function model for nine months and its value was ME=-0.00851  negative That is, most of the errors are negative, which is evidence that the approved prediction gives optimistic results.

الکشف عن القیم المتطرفة فی نموذج الانحدار الخطی مع التطبیق على بیانات تلوث میاه الآبار أطراف مدینة الموصل

Saja marwan ismail; Safwan ناظم Rashed

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 114-127
DOI: 10.33899/iqjoss.2022.174334

      The research idea is concerned with identifying the effect of outliers on the parameters of the multiple linear regression analysis model. Where the outliers values that are present in the data are detected and diagnosed if they are in the independent variables or the dependent variable, which causes an impact on the estimation of the parameters of the studied model.
 The extreme data types and methods of processing them have been identified to obtain a better model with high efficiency or reduce the impact of These values on the model,The MSE standard was developed for the purpose of comparing treatment methods and was applied to real data taken from the Dams and Water Resources Research Center, University of Mosul. Suggested by (شاکر،2009) is the best in detection among the methods that have  been used . 

معالجة عدم استقراریة السلسلة الزمنیة - مراجعة مقال-

Alla abd alsatar; Nada Nazar Alobaidi; Zainab Tawfeq

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2022, Volume 19, Issue 1, Pages 128-142
DOI: 10.33899/iqjoss.2022.174335

the    time series is a problem in econometric analysis as the statistical properties of series analysis are lost when using unstable time series. The research aims to present several methods for dealing with stability, including (Box Jenkins, Exponential Smoothing, Double Exponential Smoothing, Exponential Smoothing Moving Averages, Fuzzy, Neural Network) and to compare the methods presented through diagnosing ARIMA models after achieving stability and choosing the best method that corresponds to the lowest values ​​of the criteria Statistics (MSE, AIC, BIC). The above-mentioned methods have been applied to daily data for the year 2020 to generate electricity from water coming from the Tigris River, and it was concluded that the (Fuzzy) method is the best for treating stability compared to other methods for having the ARIMA model (0,1,3) corresponding to the lowest values ​​of the criteria Statistics (MSE=0.572, AIC=-196.4536, BIC=-0.6931).

Statistical Analysis of Geometric Stochastic Process with Application

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2012, Volume 12, Issue 1, Pages 166-188
DOI: 10.33899/iqjoss.2012.60242

يُعَدُّ موضوع العملية التصادفية الهندسية من المواضيع التي تلاقي اهتماما كبيراً وواسعاً لدى العديد من الباحثين في الوقت الحاضر لما له من أهمية في شتى المجالات المختلفة. وتُعَدُّ العملية الهندسية تعميماً لعملية التجديد.
لقد خُصِصَ هذا البحث لدراسة العملية الهندسية وتحليلها ، والمقارنة بين نموذج العملية الهندسية ونموذج عملية التجديد، فضلاً عن تقدير الدالة الهندسية من خلال استخدام الحل العددي والحل التقريبـــــي. وتضمن البحث تطبيقاً واقعياً لحالات الإصابة بالتهاب الكبد الفيروسي نوعي A وB في محافظة نينوى. وقد تم إجراء تحليل إحصائي للعملية الهندسية، واختبار ملاءمَة البيانات للعملية الهندسية، وتم تقدير العدد المتوقَّع لحالات الإصابة بالتهاب الكبد الفيروسي نوع A وB مع المقارنة بين طرائق التقديـــر.
وقد بين البحث أن العملية الهندسية ملائِمةُ للبيانات وللأنواع كافة، وأنّ نموذج العملية الهندسية أفضل من نموذج عملية التجديد. كما توصل إلى أن العدد المتوقَّع لحالات الإصابة بالتهاب الكبد الفيروسي باستخدام الحل العددي أفضل وأكثر دقةً من استخدام الحل التقريبي في التقدير.

Analysis and Modeling Time Series of Water Flow into Mosul City A Comparative Study

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2010, Volume 10, Issue 2, Pages 1-32
DOI: 10.33899/iqjoss.2010.28410

This paper presents fits for neural network model , and comparative resulting forecasts with those obtained from Box-Jenkins Method. We use time series data of Tigris's monthly flow into Mosul city from 1950-1995. To perform a comparative . forecasting work through the Box-Jenkins and neural network doesn't mean working with two different or competing aspect ; on the contrary choosing a proper architecture of neural net works requires using the skills of statistical modeling . As for application , Box-Jenkins Method has given more appropriate forecasts than those given by feed forward artificial neural network . We used Minitab and SPSS programs in the statistical aspect and Alyuda program in the neural network aspect.

New CG Method for Large-Scale Unconstrained Optimization Based on Nazareth theorem

Khalil . K. Abbo

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2008, Volume 8, Issue 1, Pages 53-65
DOI: 10.33899/iqjoss.2008.31676

In this paper we present new conjugate gradient method for computing the minimum value of differentiable real valued function in n variables ,this method derived from Nazareth theorem , which uses the equivalence of CG and Qusi–Newton methods on quadratic function also the descent property and Conjucy conditions are proved and compared with some well know CG method showing considerable improvement .

Create Hybrid System (Artificial Neural Networks and Fuzzy System) tp Arrange Websites According to there Quality

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2010, Volume 10, Issue 1, Pages 473-494
DOI: 10.33899/iqjoss.2010.29144

The main of this study is to give model to estimate Websites quality by Artificial Neural Network and fuzzy system to arrange these websites according to there quality depending on the values that get it during the application of the model on these webs, this models contain the most important element suggested for quality criteria like the content quality, availability, reliability, performances and some other elements that must took care when estimating websites with possibility to apply it on all webs by using numeral numbers to meager these categories, in order to get a syntactic model can depended on in estimating websites for easy access to good websites and notarization information can use it in scientific research

Comparison between the method of Fuzzy Control and Discriminate Function in the classification of some wells Nineveh

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2011, Volume 11, Issue 2, Pages 315-330
DOI: 10.33899/iqjoss.2011.27628

In this study, the construction of a Fuzzy Inference Control to determine the validity of the quality of ground water wells of some of Nineveh province, through a series of observations that were obtained from the areas under study. To illustrate the importance of the model it was compared with the Discriminate Function that classify the individual to the right community. The model , has proved a model of control Fuzzy high efficiency in the determination of the validity of each well is compared to a model Discriminate Function was the only classification of the wells under study where there it is valid or invalid to drink, as well as easy construction of the computational procedures required to build a Fuzzy Inference model compared to complex computational procedures required by the Discriminate Function. The configured model can be used in future to distinguish the quality of any groundwater wells based on qualitative characteristics of the waters.
Keyword: Fuzzy Control, Discriminate Function, groundwater.

Using Markov Chains in Medical Field

Abd Al-Gafoor G. Al-Obeady; Ammar Y. Suleman

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2018, Volume 15, Issue 1, Pages 107-120
DOI: 10.33899/iqjoss.2018.159249

تم فی ىذا البحث د ا رسة السمسمة الزمنیة لعدد الإصابات بمرض ذات الرئة کمتسمسمة
مارکوف ، وذلک بوضع افت ا رضات عمى عدد الإصابات لصیاغة المسألة وفق نموذج متسمسمة
مارکوف بالاعتماد عمى عدد الحالات التی تمثل الظاىر. وبعد إیجاد الصفات الإحصائیة لیذه السمسمة
تبین أنیا ثبوتیة ) Ergodic ( ، وتم إیجاد التوزیع المستقر ) Stationary distribution ( لیذه
السمسمة .

Analysis and Modeling Time Series of Water Flow into Mosul City A Comparative Study

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2010, Volume 10, Issue 2, Pages 1-32
DOI: 10.33899/iqjoss.2010.28410

This paper presents fits for neural network model , and comparative resulting forecasts with those obtained from Box-Jenkins Method. We use time series data of Tigris's monthly flow into Mosul city from 1950-1995. To perform a comparative . forecasting work through the Box-Jenkins and neural network doesn't mean working with two different or competing aspect ; on the contrary choosing a proper architecture of neural net works requires using the skills of statistical modeling . As for application , Box-Jenkins Method has given more appropriate forecasts than those given by feed forward artificial neural network . We used Minitab and SPSS programs in the statistical aspect and Alyuda program in the neural network aspect.

Using Markov Chains in Medical Field

Abd Al-Gafoor G. Al-Obeady; Ammar Y. Suleman

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2018, Volume 15, Issue 1, Pages 107-120
DOI: 10.33899/iqjoss.2018.159249

تم فی ىذا البحث د ا رسة السمسمة الزمنیة لعدد الإصابات بمرض ذات الرئة کمتسمسمة
مارکوف ، وذلک بوضع افت ا رضات عمى عدد الإصابات لصیاغة المسألة وفق نموذج متسمسمة
مارکوف بالاعتماد عمى عدد الحالات التی تمثل الظاىر. وبعد إیجاد الصفات الإحصائیة لیذه السمسمة
تبین أنیا ثبوتیة ) Ergodic ( ، وتم إیجاد التوزیع المستقر ) Stationary distribution ( لیذه
السمسمة .

Evaluating the Area of a Circle and the Volume of a Sphere by Using Monte Carlo Simulation

Abd Al- Kareem I. Sheet

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2008, Volume 8, Issue 2, Pages 48-62
DOI: 10.33899/iqjoss.2008.31429

In this reseach Monte Carlo simulation is used to calculate the area of any circle as well as the volume of any sphere numerically. Different functions are considered to test the performance of this method, in addition to some improvement to give more satisfactory results.

Estimation of Reliability Function for Complete Data - Article Review

Shaimaa Waleed

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2019, Volume 16, Issue 3, Pages 25-38
DOI: 10.33899/iqjoss.2019.164172

The theory of reliability is one of the important theories that is attracting great interest in many researchers at present because of its importance in various fields of life especially in determining the age of a particular device and its efficiency and the addition of applications in the field of radar and atmospheric and astronomical observation. The growing interest in reliability studies is due to the rapid technical and technological development and the use of complex systems in various fields. This paper reviews the article of reliability in terms of the reliability function for complete data  of one of the failure time distributions (weibull distribution) and its parameters in different methods using simulation.

Comparison between Scheduling Algorithms of Independed Processing with a proposed algorithm

IRAQI JOURNAL OF STATISTICAL SCIENCES, 2010, Volume 10, Issue 1, Pages 385-400
DOI: 10.33899/iqjoss.2010.29126

This paper investigates the analysis of scheduling algorithm of independed processing like the Longest Processing Time Scheduling algorithm(LPT) and Shortest Processing Time Scheduling algorithm(SPT) and walking a comparison between them with a proposed algorithm depending on the measuring length scheduling of each of algorithms to get the ideal solution through applying some examples.

Publisher: University of Mosul

Email:  jstascimosul@gmail.com

Editor-in-chief: Assistant Professor Dr. Heyam A. Hayawi

Print ISSN: 1680-855X

Online ISSN: 2664-2956

Keyword Cloud