This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squares method (FGLS) and the mean group method (MG) were used, and then the efficiency of the extracted estimators was compared in the case of mixed random parameters and the method that gives us the efficient estimator was chosen. Real data was applied that included the per capita consumption of electric energy (Y) for five countries, which represents the number of cross-sections (N = 5) over nine years (T = 9), so the number of observations is (n = 45) observations, and the explanatory variables are the consumer price index (X1) and the per capita GDP (X2). To evaluate the performance of the estimators of the (FGLS) method and the (MG) method on the general model, the mean absolute percentage error (MAPE) scale was used to compare the efficiency of the estimators. The results showed that the mean group estimation (MG) method is the best method for parameter estimation than the (FGLS) method. Also, the (MG) appeared to be the best and best method for estimating sub-parameters for each cross-section (country).
Abstract
The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.
the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac
... Show MoreThis experiment was conducted to examine the effects of injected gibberellic acid GA3 in subcutaneous of hens neck and supplemental vitamin D3 to control basal diet on productive performance and egg shell thickness ,relative weight of egg shell of aged laying hens. Two hundred and seventy Lohmann Brown laying hens at 73 weeks of age were randomly assigned to three treatments groups. Each treatment consist of three replicates (30 hens / replicate). The treatments were : T1 control were injected subcutaneous with 0.2 ml / kg of body weight of ethanol: sesame oil solution, T2 and T3 were injected subcutaneous with 0.2 ml / kg of body weight of ethanol: sesame oil solution which contained 400 μg GA3/ kg of body weight /week during 8 weeks (tre
... Show MoreNew biscarboxylato zwitterionic ligands, namely bis(N-carboxylatoethyl)-4,4 -dipyridinum) L1 and bis(Ncarboxylatopropyl)-)-4,4 -dipyridinum) L2, were synthesized from the reaction of 4,4 -dipyridine with 3-bromopropanoic acid and 4-bromobutanoic acid, respectively. The reaction of these ligands and the azido coligand with some metal ions resulted in the formation of polymeric complexes of general formulae [Cr2(Ln)(N3)4]Cl2·H2O and [M2(Ln)(N3)4] xH2O, where (M = Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II); n = 1, 2; x = 1, 1, 1, 1, 0, 1, and 1, respectively.) The oxygens of the carboxylato group are coordinated to the metal ion in a bidentate fashion. The mode of bonding and overall geometry of the complexes were determin
... Show MoreSalicylaldehyde was react with 4-amino-2,3-dimethyl-1-phenyl-3-pyrazoline-5-on to produce the Schiff base ligand 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on (L). The prepared ligand was identified by Microelemental Analysis, and FT.IR, UV-Vis spectroscopic techniques. A new complexes of Fe(III),Co(II),Ni(II),Cu(II),Ce(III) and Pb(II) with mixed ligands of dithizone (DTZ) and Schiff base were prepared in aqueous ethanol with a 2:2:1 M:L:DTZ. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition biological activity of the ligands and complexes against two selected type of bacteria
... Show MoreA Schiff base ligand (L) was used as primary ligand and potassium anthranilate (Anth) was used as the secondary ligand in the molar ratio M: L:2Anth to synthesize a new platinum(IV) mixed-ligand complex [Pt(L)(Anth)₂]Cl₂. The Schiff base ligand was synthesized by the condensation of 4-Aminoantipyrine with 4-Hydroxybenzaldehyde and was verified as a bidentate ligand. The UV-visible, FT-IR, 1 H NMR, 13 C NMR, CHN elemental analysis, molar conductance, chloride ion determination and melting point measurements were used to characterize the ligand and the complex. The results of the molar conductance showed that the electrolytic behavior was 1:2, where the two chloride ions were present outside the coordination sphere, while the spectroscopi
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct