In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection criteria, as- sessing the correct detection of zero coefficients and the false omission of nonzero coef- ficients. A practical application involving financial data from the Baghdad Soft Drinks Company demonstrates their utility in identifying key predictors of stock market value. The results indicate that MAVE-SCAD performs well in high-dimensional and complex scenarios, whereas MAVE-ALASSO is better suited to small samples, producing more parsimonious models. These results highlight the effectiveness of these two methods in addressing key challenges in semiparametric modeling
This study was aimed to produce bacteriocin from Bacillus. licheniformis isolated from local soil of corn and sunflower fields and using as antimicrobial agent . Fourteen of local isolates of Bacillus sp. were obtained and ability of these isolates for growth on Brain heart infusion agar (BHI) at 550C were tested. Isolate C4 was revealed high growth density in comparison with other isolates. Isolate C4 was identified as Bacillus licheniformis according to morphological, cultural and biochemical tests, Moreover genetic analysis for 16S rRNA gene and given accession number MT192715.1 in GenBank of NCBI . Production of bacteriocin from this isolate was carried out in Luria Broth (LB) and partially purified by precipitation with 30-70 % saturat
... Show MoreIn the current study, we investigate the effect of (La) substitution instead of (Cu) on the properties of the superconductor compound (Bi2Sr2Ca2Cu3-xLaxO10+δ) with (x=0,0.05,0.1,0.15,0.2). The samples were prepared by solid state reaction method(SSR). Xray diffraction technique (XRD) was used to estimate the structural properties of the specimens which show an orthorhombic crystalline structure for all the specimens. The results show that the change in ( La) concentration leads to decrease the concentration of (Bi-2223), increment in (Bi-2212 ) and(Bi-2201) with appearance of some impurities. Also decrease the critical temperature(Tc) with the increase
... Show MoreThis investigation was carried out to examine the effect of replacing partial of flour by dried Lentils (Lens culinaris) to white flour in different percentages on the chemical, sensory and storage properties of the Laboratory bread. The results revealed that replacing 0% than wheat flour by lentil powder (1) control was high significan than the replacing 25 and 35% than wheat flour by lentil powder ( 4 and 5) in flavor and chewiness . The results of sensory evaluation showed that replacing 4 were high significan different than that of replacing 1 in external layer colour. Other replacing percentages, however, did not show significant differences of in comparison with control . In regards with chemical analysis of Iron and copper, i
... Show MoreThe estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To
... Show MoreIn this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.
The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu
... Show MoreThere is an assumption implicit but fundamental theory behind the decline by the time series used in the estimate, namely that the time series has a sleep feature Stationary or the language of Engle Gernger chains are integrated level zero, which indicated by I (0). It is well known, for example, tables of t-statistic is designed primarily to deal with the results of the regression that uses static strings. This assumption has been previously treated as an axiom the mid-seventies, where researchers are conducting studies of applied without taking into account the properties of time series used prior to the assessment, was to accept the results of these tests Bmanueh and delivery capabilities based on the applicability of the theo
... Show MoreIn this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this in
... Show More