The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

The aim of this work is to evaluate the onc-electron expectation values < r > from the radial electronic density funetion D(r) for different wave ?'unctions for the 2s state of Li atom. The wave functions used were published in 1963,174? and 1993 , respectavily. Using " " ' wave function as a Slater determinant has used the positioning technique for the analysis open shell system of Li (Is2 2s) State.

The study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.

In this paper, visible image watermarking algorithm based on biorthogonal wavelet
transform is proposed. The watermark (logo) of type binary image can be embedded in the
host gray image by using coefficients bands of the transformed host image by biorthogonal
transform domain. The logo image can be embedded in the top-left corner or spread over the
whole host image. A scaling value (α) in the frequency domain is introduced to control the
perception of the watermarked image. Experimental results show that this watermark
algorithm gives visible logo with and no losses in the recovery process of the original image,
the calculated PSNR values support that. Good robustness against attempt to remove the
watermark was s

The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different sets of features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used as a dataset f

This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ₁and  λ₂  , also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i