In this research, we present a nonparametric approach for the estimation of a copula density using different kernel density methods. Different functions were used: Gaussian, Gumbel, Clayton, and Frank copula, and through various simulation experiments we generated the standard bivariate normal distribution at samples sizes (50, 100, 250 and 500), in both high and low dependency. Different kernel methods were used to estimate the probability density function of the copula with marginal of this bivariate distribution: Mirror – Reflection (MR), Beta Kernel (BK) and transformation kernel (KD) method, then a comparison was carried out between the three methods with all the experiments using the integrated mean squared error. Furthermore, some charts were used to support this comparison such as copula contours to spread the correlation before and after estimations. The simulation results show preference of the transformation kernel estimators (KDE) among all the estimation methods, which also proved that copulas are highly flexible models for high dependency especially of the Gaussian type.
Background: Oral lichen planus (OLP) is a chronic inflammatory disease with an autoimmune inflammatory pathogenesis. The purpose of this study was to evaluate the role of angiogenesis in the pathogenesis of OLP, using CD34 stain to highlight the blood vessels for measuring the microvessel density (MVD) as well as to evaluate the relation of this marker with the degree of inflammation Materials and Methods: Immunohistochemical (IHC) staining technique was used to evaluate angiogenesis using CD34 in 46 paraffin blocks 10 of them obtained from normal mucosa and 36 from cases diagnosed as lichen planus , 20 of them diagnosed as Reticular type while 16 as erosive type. Severity of inflammation was divided into mild, moderate and severe accordi
... Show MoreIn this work, the Whittaker wave functions were used to study the nuclear density distributions and elastic electron scattering charge form factors for proton-rich nuclei and their corresponding stable nuclei (10,8B, 13,9C, 14,12N and 19,17F). The parameters of Whittaker’s basis were fixed to generate the experimental values of available size radii. The Whittaker basis was connected to harmonic-oscillator basis through boundary condition at match point. The nuclear shell model was opted with pure configuration for all studied nuclei to compute aforementioned studied quantities except 10
Studies from our laboratory have shown that Δ9-Tetrahydrocannabinol (THC), an ingredient found in marijuana plant Cannabis sativa, can attenuate acute lung injury induced by Staphylococcus enterotoxin B (SEB). In the current study, we investigated the role of THC on the metabolism of SEB-activated lymphocytes. To this end, we determined metabolic potential of SEB-activated lymphocytes treated with vehicle or THC by performing the Cell Mito Stress Test. The oxygen consumption rate (OCR) in THC-treated cells was decreased when compared to vehicle-treated group whereas the extracellular acidification rate (ECAR) was similar in both the groups. Specifically, electron transport chain inhi
The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.
In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show MoreTheresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had
... Show MoreThe research took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS
... Show MoreIn this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.