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Robust Estimation OF The Partial Regression Model Using Wavelet Thresholding
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            Semi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavelet threshold and the PLM estimation method with the Speakman estimation and Nadarya-Watson smoothing, using simulation experiments at different sample sizes and contaminated ratios.

     The mean square error criterion was employed to compare the two methods. The robust method is more efficient in obtaining robust estimators than the PLM estimation method

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Robust Estimations for power Spectrum in ARMA(1,1) Model Simulation Study
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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

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Ridge regression method with some classical methods to estimate the parameters of Lomax distribution by simulation
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Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

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Publication Date
Sun Jul 01 2012
Journal Name
Ieee Transactions On Geoscience And Remote Sensing
Echo Amplitude Normalization of Full-Waveform Airborne Laser Scanning Data Based on Robust Incidence Angle Estimation
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Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Tue Dec 01 2020
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Offline signatures matching using haar wavelet subbands
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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

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Engineering
Comparative Analysis of The Combined Model (Spatial and Temporal) and Regression Models for Predicting Murder Crime
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This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem
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Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Estimation Activity And Partial Purification Of Leucine Amino Peptidase (Lap) In Patients Wiith Diabetic Nephropathy
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Leucine aminopepotidase (LAP)[EC:3.4.11.1] activity has been assayed in (50) serum samples of patients with diabeties naphrophathy D.N (non-insulin dependent diabetic (NIDD) , and (50)serum sample of healthy individuals without any clinically detectable diseases have been as control group. The aim of this study is to measure leucine aminopeptidase activity and partially purifying the enzyme from sera of patients with diabetes nephropathy The results of this study revealed that Leucine aminopeptidase (LAP) activity of nephropathy patient’s serum shows a high signifiacant increase (p < 0.001) compared to that of the healthy subjects.LAP was purified from the serum of patients with diabetes nephropathy by dialysis and gel filtration (Se

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Publication Date
Tue Apr 04 2023
Journal Name
Journal Of Techniques
Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model
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Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides
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 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one

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