Abstract

The analysis of Least Squares: LS is often unsuccessful in the case of outliers ​​in the studied phenomena. OLS will lose their properties and then lose the property of Beast Linear Unbiased Estimator (BLUE), because of the Outliers have a bad effect on the phenomenon. To address this problem, new statistical methods have been developed so that they are not easily affected by outliers. These methods are characterized by robustness or (resistance). The Least Trimmed Squares: LTS method was therefore a good alternative to achieving more feasible results and optimization. However, it is possible to assume weights that take into consideration the location of the outliers ​​in the data and det

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distrib

The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

The dependence of the energy losses or the stopping power for the ion contribution in D- T hot plasma fuels upon the corresponding energies and the related penetrating factorare arrive by using by a theoretical approximation models. In this work we reach a compatible agreement between our results and the corresponding experimental results.

The research dealt with the effectiveness of prediction and foresight in design as a phenomenon that plays a role in the recipient's engagement with the design, as it shows the interaction between the recipient and the interior space. The designer is keen to diversify his formal vocabulary in a way that secures visual values that call for aesthetic integration, as well as securing mental and kinetic behavioral understanding in the interior space.
As the designer deals with a three-dimensional space that carries many visual scenes, the designer should not leave anything from it without standing on it with study and investigation, and puts the user as a basic goal as he provides interpretive data through prediction and foresight that le

New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.