In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best
Bladder cancer is the ninth most common malignancy all over the world. Immune picture is important in predicting clinical outcome with bladder cancer, so the aim of the present study was to investigate the number of killer cells in the tissue of the patients with the malignant and benign bladder cancer before treatment by using an antigen retrieval immunohistochemical method on archived bladder tumors tissue. In our study, the number of the patients tissue with malignant cancer that staining by immunohistochemistry of NK cells (20%) was lower than in benign (80%) (p≤0.01). The results of the present study were indicated that the lower level of the NK cells in the malignant tissues may be leads to impaired anti-tumor immune response tow
... Show MoreMaximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
... Show MoreIn the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.
Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.
Background: management modalities for liver metastasis from primary breast cancer are evolving steadily but systemic chemotherapy remains the mainstay of treatment.
Patients and methods: 30 patients with breast carcinoma and liver metastasis managed at (Baghdad teaching hospital) during the period from Jan. 2005 to Jan. 2007.
Results: 16 patients showed response to chemotherapy. 20% complete response was found and 33% showed partial response 57% went into progressive disease. The duration of response lasted for less than six months in 4 patients and more than six months in two patients.
Conclusion: chemotherapy remains the mainstay of treatment of liver metastasis but new modalities of treatment add much
The Bouguer gravity and magnetic RTP data were used to detect the depth of basement rocks in middle and south Diyala Province, east Iraq. The depth of the basement rocks was calculated by using the Source Parameter Imaging (SPI) method. New attempt is achieved to applied the SPI technique to the gravity values to estimate the depth of basement rocks. The depths of basement map derived from gravity data range 8-14 km, the depth of basement map derived from magnetic data range 9-13.5 km and the basement depth prepared by C.G.G, 1974 range 9-11 km. The derived maps from SPI method and that prepared by C.G.G, 1974 show good matching in the distribution of the depths of the study area. This study showed that basement’s depth range from
... Show MoreThe prospective study has been designed to determine some biomarkers in Iraqi female patients with
breast cancer. The current study contained 30 patients whose tissue samples have been collected from
hospitals in Medical City in Baghdad after consent patients themselves and used immunohistochemical
technique to determine these markers. The results showed a significant correlation between ER and PR tissue
markers (Sig = 0.000) and a significant correlation between cyclin E phenotype and cyclin E intensity (Sig =
0.001).
This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical
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Abstract
Rayleigh distribution is one of the important distributions used for analysis life time data, and has applications in reliability study and physical interpretations. This paper introduces four different methods to estimate the scale parameter, and also estimate reliability function; these methods are Maximum Likelihood, and Bayes and Modified Bayes, and Minimax estimator under squared error loss function, for the scale and reliability function of the generalized Rayleigh distribution are obtained. The comparison is done through simulation procedure, t
... Show MoreSegmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in
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