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NONPARAMETRIC ESTIMATION IN DOUBLY GEOMETRIC STOCHASTIC PROCESSES
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A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk and ln Xk, as well as the linear regression method, where μ and σ2 are the mean and variance of X1, respectively. A real-world example is used to demonstrate the process. Furthermore, the estimators' output is evaluated using a real-world example. © 2021 DAV College. All rights reserved.

Scopus
Publication Date
Wed Dec 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATING NONPARAMETRIC AUTOREGRESSIVE CURVE BY SMOOTHING SPLINES METHOD
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Scopus
Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some NONPARAMETRIC ESTIMATORS FOR RIGHT CENSORED SURVIVAL DATA
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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 parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

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Crossref
Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

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Crossref
Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
A Stochastic Differential Equations Model for the Spread of Coronavirus COVID-19): The Case of Iraq
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In this paper, we model the spread of coronavirus (COVID -19) by introducing stochasticity into the deterministic differential equation susceptible  -infected-recovered (SIR model). The stochastic SIR dynamics are expressed using Itô's formula. We then prove that this stochastic SIR has a unique global positive solution I(t).The main aim of this article is to study the spread of coronavirus COVID-19 in Iraq from 13/8/2020 to 13/9/2020. Our results provide a new insight into this issue, showing that the introduction of stochastic noise into the  deterministic model for the spread of COVID-19 can cause the disease to die out, in scenarios where deterministic models predict disease persistence. These results were also clearly ill

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Robust Blind Watermarking Technique Against Geometric Attacks for Fingerprint Image Using DTCWT-DCT
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In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coeffi

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Impact of geometric factor in accumulation factor measurements of gamma rays
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In this research a study process to calculate the factor accumulation of gamma rays for aluminum and exporters cobalt 60 Mika Atktron volts and actively radiation Vdrh 1.406 Mika Bq been studying the effect of the angle of reimbursement and the distance between the shield and detector In measurements factor accumulation Adhrt results in line with the theoretical results published

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Publication Date
Fri Jul 19 2019
Journal Name
Iraqi Journal Of Science
Mann Iteration Processes on Uniform Convex n-Banach Space
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Let Y be a"uniformly convex n-Banach space, M be a nonempty closed convex subset of Y, and S:M→M be adnonexpansive mapping. The purpose of this paper is to study some properties of uniform convex set that help us to develop iteration techniques for1approximationjof"fixed point of nonlinear mapping by using the Mann iteration processes in n-Banachlspace.

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Mathematics Research
Effect of Some Geometric Transfers on Homology Groups
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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Some Geometric Properties of a Hyperbolic Univalent Function
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In this paper, we analyze several aspects of a hyperbolic univalent function related to convexity properties, by assuming  to be the univalent holomorphic function maps of the unit disk  onto the hyperbolic convex region  ( is an open connected subset of). This assumption leads to the coverage of some of the findings that are started by seeking a convex univalent function distortion property to provide an approximation of the inequality and confirm the form of the lower bound for . A further result was reached by combining the distortion and growth properties for increasing inequality  . From the last result, we wanted to demonstrate the effect of the unit disk image on the condition of convexity estimation

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Publication Date
Fri Mar 04 2022
Journal Name
Trends In Sciences
Asymptotic Stability of 3D Stochastic Positive Linear Systems with Delays
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The article emphasizes that 3D stochastic positive linear system with delays is asymptotically stable and depends on the sum of the system matrices and at the same time independent on the values and numbers of the delays. Moreover, the asymptotic stability test of this system with delays can be abridged to the check of its corresponding 2D stochastic positive linear systems without delays. Many theorems were applied to prove that asymptotic stability for 3D stochastic positive linear systems with delays are equivalent to 2D stochastic positive linear systems without delays. The efficiency of the given methods is illustrated on some numerical examples. HIGHLIGHTS Various theorems were applied to prove the asymptoti

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