In this article we propose a general Bayesian estimation framework for the Birnbaum-Saunders Quantile Regression (BSQ) model which is used to analyze asymmetric and heterogeneous economic data. In this work, the novel aspect is the joint incorporation of several existing surrogate structures (with different degrees of approximation) and decision-theoretic loss functions (with direct impact on estimation performance trade-offs) under a common BSQ framework conducive to systematic testing of their effect on quantile estimation performance. We consider two previous prior specifications which are Jeffreys prior and weakly informative priors together with three loss functions quadratic, LINEX and the proposed quadratic-logarithmic loss function. Iraqi economic data analysis demonstrates significant disparities in independent variable impacts across quantiles, confirming heterogeneous distribution. The results show further that Jeffreys prior yields more consistent estimates in most quantiles, whereas weakly informative priors give better coverage under the tail. Also, this highlights the importance of choosing a loss function and motivates asymmetric and hybrid loss functions for improved accuracy, especially in extreme quantiles. This contribution expands upon previous works by introducing a new general comparative framework that overextends the potential of Bayesian BSQ modelling, providing robustness and flexibility in such context with significant practical function resulting estimation improves in economic real-world applications.
Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
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The efficiency of management is determining factor for the success or failure of agricultural projects generally and Livestock particularly achieving its objectives. Therefore, this research came to diagnose the most important variables that determine the efficiency of management using the probability regression models to measure the probability of management efficient of broilers production projects using random sample included (60) broilers projects represented 11.6% of Baghdad province (research community) in 2016. After estimating the relationship between the management efficiency (descriptive dependent variable) and the independent variables affecting it (age, educational level, production index (PI), experience). The results
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The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show MoreIn this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser
The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser
The research work represent a fast and simple method for the determination of methionine using chemiluminescence for the methionine-sodium hydroxide-luminol for the generation of a chemiluminesecent derivative of luminal. The emission was measured by continuous flow analysis made sample size of 83µL was used.Response versus concentration extended from 0.2-20 mM.L-1 with a percentage linearity of 96.17% or with 99.17% percentage of linearity for the range 0.6-20 mM.L-1. Reaching to a L.O.D. at (S/N=3) for 5 µM.L-1 from the gradual dilution for the minimum concentration in the calibration graph with a repeatability of less than 0.5% (n=10). A comparison was made between the new developed method with the classical method for the spectrophoto
... Show MoreThis study demonstrates a sustainable, "trash-to-treasure" approach by synthesizing silica (SiO2) and alumina (Al2O3) nanoparticles (30–80 nm) from local waste materials—specifically bentonite clay and aluminum wire waste—and evaluating their performance as eco-friendly additives in 350 mL water-based drilling fluids at concentrations ranging from 0 to 1 g. Tested under harsh subsurface conditions, the incorporated nanoparticles significantly enhanced the fluids' rheological properties, lubricity, filtration control, and swelling inhibition, with performance scaling alongside nanoparticle concentration. Notably, at a 1 g dosage, the fluid's yield point spiked from a baseline of 9 to 42 for SiO2 and 32 for (Al2O3), while h
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