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The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics

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Computers, Materials & Continua 2020年第12期65卷 2049-2064页

作者： Ahmed Bachir ibrahim mufrah almanjahie Mohammed Kadi Attouch Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Djillali Liabes University Sidi Belabbes22000Algeria

It is well known that the nonparametric estimation of the regression function is highly sensitive to the presence of even a small proportion of outliers in the *** solve the problem of typical observations when the covariates of the nonparametric component are functional,the robust estimates for the regression parameter and regression operator are *** main propose of the paper is to consider data-driven methods of selecting the number of neighbors in order to make the proposed processes fully *** use thek Nearest Neighbors procedure(kNN)to construct the kernel estimator of the proposed robust *** some regularity conditions,we state consistency results for kNN functional estimators,which are uniform in the number of neighbors(UINN).Furthermore,a simulation study and an empirical application to a real data analysis of octane gasoline predictions are carried out to illustrate the higher predictive performances and the usefulness of the kNN approach.

关键词： Functional data analysis quantile regression kNN method uniform nearest neighbor(UNN)consistency functional nonparametric statistics almost complete convergence rate

L-Moments Based Calibrated Variance Estimators Using Double Stratified Sampling

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Computers, Materials & Continua 2021年第9期68卷 3411-3430页

作者： Usman Shahzad Ishfaq Ahmad ibrahim mufrah almanjahie Nadia H.Al–Noor Department of Mathematics and Statistics International Islamic UniversityIslamabad44000Pakistan Department of Mathematics and Statistics PMAS-Arid Agriculture UniversityRawalpindi46300Pakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Department of Mathematics College of ScienceMustansiriyah UniversityBaghdad10011Iraq

Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values,and thus its results cannot be relied *** momentum from Koyuncu’s recent work,the present paper focuses first on proposing two classes of variance estimators based on linear moments(L-moments),and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments(L-location,L-cv,L-variance).Three populations are taken into account to assess the efficiency of the new *** first and second populations are concerned with artificial data,and the third populations is concerned with real *** percentage relative efficiency of the proposed estimators over existing ones is *** the presence of extreme values,our findings depict the superiority and high efficiency of the proposed classes over traditional ***,when auxiliary data is available along with extreme values,the proposed classes of estimators may be implemented in an extensive variety of sampling surveys.

关键词： Variance estimation L-moments calibration approach double sampling stratified random sampling

A New Class of L-Moments Based Calibration Variance Estimators

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Computers, Materials & Continua 2021年第3期66卷 3013-3028页

作者： Usman Shahzad Ishfaq Ahmad ibrahim mufrah almanjahie Nadia H.Al Noor Muhammad Hanif Department of Mathematics and Statistics International Islamic UniversityIslamabad46000Pakistan Department of Mathematics and Statistics PMAS-Arid Agriculture UniversityRawalpindi46300Pakistan Department of Mathematics King Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Department of Mathematics College of ScienceMustansiriyah UniversityBaghdad10011Iraq

Variance is one of themost important measures of descriptive statistics and commonly used for statistical *** traditional second-order central moment based variance estimation is a widely utilized ***,traditional variance estimator is highly affected in the presence of extreme *** this paper initially,proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics(L-location,Lscale,L-CV)and auxiliary *** is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than adapted *** data is considered for assessing the performance of the proposed *** also demonstrated an application related to apple fruit for purposes of the *** artificial and real data sets,percentage relative efficiency(PRE)of the proposed class of estimators with respect to adapted ones are *** PRE results indicate to the superiority of the proposed class over adapted ones in the presence of extreme *** this manner,the proposed class of estimators could be applied over an expansive range of survey sampling whenever auxiliary information is available in the presence of extreme values.

关键词： L-moments variance estimation calibration approach stratified random sampling

New Improved Ranked Set Sampling Designs with an Application to Real Data

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Computers, Materials & Continua 2021年第5期67卷 1503-1522页

作者： Amer ibrahim Al-Omari ibrahim M.almanjahie Department of Mathematics Faculty of ScienceAl al-Bayt UniversityMafraqJordan Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia

This article proposes two new Ranked Set Sampling(RSS)designs for estimating the population parameters:Simple Z Ranked Set Sampling(SZRSS)and Generalized Z Ranked Set Sampling(GZRSS).These designs provide unbiased estimators for the mean of symmetric *** is shown that for non-uniform symmetric distributions,the estimators of the mean under the suggested designs are more efcient than those obtained by RSS,Simple Random Sampling(SRS),extreme RSS and truncation based RSS ***,the proposed RSS schemes outperform other RSS schemes and provide more efcient estimates than their competitors under imperfect *** suggested mean estimators under perfect and imperfect rankings are more efcient than the linear regression estimator under *** proposed RSS designs are also extended to cover the estimation of the population *** data is used to examine wthe usefulness and efciency of our estimators.

关键词： Ranked set sampling unbiased estimator simple random sampling mean squared error efciency imperfect ranking

Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

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Computers, Materials & Continua 2021年第4期67卷 285-301页

作者： Amer ibrahim Al-Omari ibrahim M.almanjahie Olena Kravchuk Department of Mathematics Faculty of ScienceAl al-Bayt UniversityMafraqJordan Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia School of Agriculture University of AdelaideAdelaideSA 5000Australia

In this paper,we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans(ASPs)where the life test is assumed to be truncated at a pre-assigned *** the new suggested ASPs,the tables of the minimum samples sizes needed to assert a specific mean life of the test units are *** addition,the values of the corresponding operating characteristic function and the associated producer’s risks are *** of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans;one data set contains the first failure of 20 small electric carts,and the other data set contains the failure times of the air conditioning system of an *** are made between the proposed acceptance sampling plans and some existing acceptance sampling plans considered in this study based on the minimum sample *** is observed that the samples sizes based on the proposed acceptance sampling plans are less than their competitors considered in this *** suggested acceptance sampling plans are recommended for practitioners in the field.

关键词： Acceptance sampling plan producer’s risk truncated life tests operating characteristic function length-biased weighted lomax distribution consumer’s risk

Quantile Version of Mathai-Haubold Entropy of Order Statistics

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Computer Modeling in Engineering & Sciences 2021年第9期128卷 907-925页

作者： ibrahim M.almanjahie Javid Gani Dar Amer ibrahim Al-Omari Aijaz Mir Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Department of Mathematical Sciences IUSTKashmir192231India Department of Mathematics Faculty of ScienceAl al-Bayt UniversityMafraq25113Jordan Department of Mathematics Govt.Degree College KilamHigher EducationJ&K192231India

Many researchers measure the uncertainty of a random variable using quantile-based entropy *** techniques are useful in engineering applications and have some exceptional characteristics than their distribution function *** order statistics,the key focus of this article is to propose new quantile-based Mathai-Haubold entropy and investigate its *** divergence measure of theMathai-Haubold is also considered and some of its properties are ***,based on order statistics,we propose the residual entropy of the quantile-based Mathai-Haubold and some of its property results are *** performance of the proposed quantile-based Mathai-Haubold entropy is investigated by simulation ***,a real data application is used to compare our proposed quantile-based entropy to the existing quantile *** results reveal the outperformance of our proposed entropy to the other entropies.

关键词： Shannon entropy Mathai-Haubold entropy quantile function residual entropy order statistics failure time reliability measures

Functional Nonparametric Predictions in Food Industry Using Near-Infrared Spectroscopy Measurement

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Computers, Materials & Continua 2023年第3期74卷 6307-6319页

作者： ibrahim M.almanjahie Omar Fetitah Mohammed Kadi Attouch Tawfik Benchikh Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Laboratory of Statistics and Stochastic Processes University of Djillali Liabes BP 89 Sidi Bel Abbes22000Algeria Medical Faculty Djillali Liabes University BP 89Sidi Bel Abbes22000Algeria

Functional statistics is a new technique for dealing with data thatcan be viewed as curves or images. Parallel to this approach, the Near-InfraredReflectance (NIR) spectroscopymethodology has been used in modern chemistryas a rapid, low-cost, and exact means of assessing an object’s chemicalproperties. In this research, we investigate the quality of corn and cookiedough by analyzing the spectroscopic technique using certain cutting-edgestatistical models. By analyzing spectral data and applying functional modelsto it, we could predict the chemical components of corn and cookie *** Functional Classical Estimation (KFCE), Kernel Functional QuantileEstimation (KFQE), Kernel Functional Expectile Estimation (KFEE),Semi-Partial Linear Functional Classical Estimation (SPLFCE), Semi-PartialLinear Functional Quantile Estimation (SPLFQE), and Semi-Partial LinearFunctional Expectile Estimation (SPLFEE) are models used to accuratelyestimate the different quantities present in Corn and Cookie dough. Theselection of these functional models is based on their ability to constructa forecast region with a high level of confidence. We demonstrate that theconsidered models outperform traditional models such as the partial leastsquaresregression and the principal component regression in terms of predictionaccuracy. Furthermore, we show that the proposed models are morerobust than competing models such as SPLFQE and SPLFEE in the sensethat data heterogeneity has no effect on their efficiency.

关键词： Functional statistics NIR chemical component kernel estimation

Industrial Food Quality Analysis Using New k-Nearest-Neighbour methods

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Computers, Materials & Continua 2021年第5期67卷 2681-2694页

作者： Omar Fetitah ibrahim M.almanjahie Mohammed Kadi Attouch Salah Khardani Laboratory of Statistics and Stochastic Processes University of Djillali LiabesSidi Bel Abbes22000Algeria Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Facultédes sciences de Tunis Laboratoire des Réseaux Intelligents et NanotechnologieTunisTunisia

The problem of predicting continuous scalar outcomes from functional predictors has received high levels of interest in recent years in many fields,especially in the food *** k-nearest neighbor(k-NN)method of Near-Infrared Reflectance(NIR)analysis is practical,relatively easy to implement,and becoming one of the most popular methods for conducting food quality based on NIR *** k-NN is often named k nearest neighbor classifier when it is used for classifying categorical variables,while it is called k-nearest neighbor regression when it is applied for predicting noncategorical *** objective of this paper is to use the functional Near-Infrared Reflectance(NIR)spectroscopy approach to predict some chemical components with some modern statistical models based on the kernel and k-Nearest Neighbour *** this paper,three NIR spectroscopy datasets are used as examples,namely Cookie dough,sugar,and tecator ***,we propose three models for this kind of data which are Functional Nonparametric Regression,Functional Robust Regression,and Functional Relative Error Regression,with both kernel and k-NN approaches to compare between *** experimental result shows the higher efficiency of k-NN predictor over the kernel *** predictive power of the k-NN method was compared with that of the kernel method,and several real data sets were used to determine the predictive power of both methods.

关键词： Functional data analysis classical regression robust regression relative error regression kernel method k-NN method near-infrared spectroscopy

Generalized Class of Mean Estimators with Known Measures for Outliers Treatment

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Computer Systems Science & Engineering 2021年第7期38卷 1-15页

作者： ibrahim M.almanjahie Amer ibrahim Al-Omari Emmanuel J.Ekpenyong Mir Subzar Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Department of Mathematics Faculty of ScienceAl al-Bayt UniversityMafraq25113Jordan Department of Statistics Michael Okpara University of AgricultureUmudikeAbiaNigeria Jammu and Kashmir Institute of Mathematical Sciences Srinagar190008India

In estimation theory,the researchers have put their efforts to develop some estimators of population mean which may give more precise results when adopting ordinary least squares(OLS)method or robust regression techniques for estimating regression *** when the correlation is negative and the outliers are presented,the results can be distorted and the OLS-type estimators may give misleading estimates or highly biased ***,this paper mainly focuses on such issues through the use of non-conventional measures of dispersion and a robust estimation ***,we have proposed generalized estimators by using the ancillary information of non-conventional measures of dispersion(Gini’s mean difference,Downton’s method and probabilityweighted moment)using ordinary least squares and then finally adopting the Huber M-estimation technique on the suggested *** proposed estimators are investigated in the presence of outliers in both situations of negative and positive correlation between study and auxiliary *** comparisons and real data application are provided to show the strength of the proposed generalized *** is found that the proposed generalized Huber-M-type estimators are more efficient than the suggested generalized estimators under the OLS estimation method considered in this *** new proposed estimators will be useful in the future for data analysis and making decisions.

关键词： Product estimators ratio estimators regression estimators ordinary least square Huber M mean squared error efficiency