A Proposed Model for Predicting Financial Loss of Private Conventional and Islamic Banks in Syria رنيم الحصري ؛ رغد الرهونجي ؛ راما الحكواتي ؛ إشراف د. علاء صالحاني
This study aimed to find a model consisting of a set of financial ratios in which each ratio has its own weight that indicate ...
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Advances in Distribution Theory, Order Statistics, and Inference
Barry Arnold has made fundamental contributions to many different areas of statistics, including distribution theory, Bayesian ...
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Advances in Mathematical and Statistical Modeling
Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal ...
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Algorithmic Learning in a Random World
This new monograph integrates mathematical theory and revealing experimental work. It demonstrates mathematically the validity ...
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Algorithms for Approximation ; Proceedings of the 5th International Conference, Chester, July 2005
Approximation methods are vital in many challenging applications of computational science and engineering. This is a collection ...
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Analysing Ecological Data
This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ...
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Applied Probability and Statistics
This text is designed for a one-semester course on Probability and Statistics. The exposition unfolds systematically from ...
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Applied Statistics Using SPSS, STATISTICA, MATLAB and R
The book provides a comprehensive coverage of the main statistical analysis topics important for practical applications such ...
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Artificial Mind System
This book is written from an engineer's perspective of the mind. "Artificial Mind System" exposes the reader to a broad ...
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Bayesian Computation with R : Introduces Bayesian modeling by use of computation using the R language
R's open source nature, free availability, and large number of contributor packages have made R the software of choice for ...
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Bayesian Core: A Practical Approach to Computational Bayesian Statistics
This Bayesian modeling book provides an operational methodology for conducting Bayesian inference, rather than focusing on ...
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Biostatistics and Microbiology: A Survival Manual
This book presents a step-by-step manner that eliminates the greatest obstacle to the learner, which is applying the many ...
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Branch-and-Bound Applications in Combinatorial Data Analysis
There are a variety of combinatorial optimization problems that are relevant to the examination of statistical data. Combinatorial ...
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Classical Methods of Statistics
Classical Methods of Statistics is a blend of theory and practical statistical methods written for graduate students and ...
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Conducting Quantitative Research In Education
provides a clear and straightforward guide for all those seeking to conduct quantitative research in the field of education, ...
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Correlated Data Analysis: Modeling, Analytics, and Applications
Presents some recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components ...
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Data Analysis Using the Method of Least Squares
The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full ...
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Data Analysis Using the Method of Least Squares
The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full ...
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Dealing with Uncertainties
Dealing with Uncertainties proposes and explains a new approach for the analysis of uncertainties. Firstly, it is shown that ...
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Deep Learning for Computational Problems in Hardware Security : Modeling Attacks on Strong Physically Unclonable Function Circuits / Pranesh Santikellur, Rajat Subhra Chakraborty
Discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware ...
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