The research is a contemporary stylistic study of the text that expresses the psychological
meanings in Nahj Al-Balaghah.
The research is divided to three chapters.
The first chapter : characteristics of psychological text.
It is about the power to influence the addressee ,that is to say ,the text influence power
connects with vulnerability and emotions inside the addressee spirit and his response to
violent effects shaking his feelings and that is represented in outbreaking of words vitality and
homogeneously. The Imam's wrath , grief , love to rightness , hatred of falsehood and
deviation from Islam arouses the words and emotions through :
1. Reduction in words and expansion in meaning by means of inspiration of the intentional
meaning.
2. Consistency and coherence: illustrates the connection between words and forms of
consistency.
3. Homogeneity between the components of the sentence to illustrate the closeness and
attachment of words by formatives and grammatical links.
4. Script overlap between The Holy Quran and Nahj Al-Balaghah in those texts.
The second chapter : coherence in The Holy Quran text whether among It's words or phrases .
The most important links are : conjunctions , conductive names , linking by meaning change ,
linking by pronouns , linking by demonstrative pronouns and linking by repetition.
The third chapter : structural phenomena in psychological text which consist : elaboration and
detailing in meaning or structural expansion of the the sentences , repetition , sequence ,
diversification in syntax composition , conformity and violation. All these phenomena are
common in the texts of Nahj Al-Balaghah.
As the process of estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .
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