The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

The objective of this research is to study experimentally and theoretically the girder vertical load share of the curved I-Girder bridges subjected to the point load in addition to the self-weigh and supper imposed dead loads. The experimental program consist of manufacturing and testing the five simply supported bridge models was scaled down by (1/10) from a prototype of 30m central span. The models carriageway central radii are 30 m, 15m or 10m. The girder spacing of the first two models is 175 mm with an overall carriageway width of 650mm. The girder spacing of the other three bridge models is 200mm with the overall carriageway width of 700 mm. The overall depth of the composite section was 164 mm. To investigate the effect of live load

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

the main of this paper is to give a comprehensive presentation of estimating methods namely maximum likelihood bayes and proposed methods for the parameter

Simulation Study

Abstract :

Robust statistics Known as, Resistance to mistakes resulting of the deviation of Check hypotheses of statistical properties ( Adjacent Unbiased  , The Efficiency of data taken from a wide range of probability distributions follow a normal distribution or a mixture of other distributions with different standard deviations.

 power spectrum function lead to, President role in the analysis of Stationary random processes, organized according to time, may be discrete random variables or continuous. Measuring  its total capacity as frequency function.

Estimation methods Share with

Background Subtraction (BGS) is one of the main techniques used for moving object detection which further utilized in video analysis, especially in video surveillance systems. Practically, acquiring a robust background (reference) image is a real challenge due to the dynamic change in the scene. Hence, a key point to BGS is background modeling, in which a model is built and repeatedly used to reconstruct the background image.

From N frames the proposed method store N pixels at location(x,y) in a buffer, then it classify pixel intensity values at that buffer using a proposed online clustering model based on the idea of relative  run length, the cluster center with the highest frequency will be adopted as the background pixel