In this paper, we show that the unbiased estimator of the certion Parameter of the selected population does not exist. First, we give a new proof of this fact for the selected normal population. We then extend the result to some other distributions belonging to one-parameteric exponential family. Whenever an unbiased estimator exists, it is shown to be a function of order statiscs.

Complex and variable nature of the river sediment yield caused many problems in prediction of the long-term sediment yield and input into the reservoirs .sediment rating curves generally used to estimate the suspended sediment load of the river and drainage basin. Since the regression equations of the sediment rating curves obtained by logarithmic retransformation and little independent variable include in this equation they also overestimate or underestimate the true load of the rivers. In this research in order to improve and develop sediment yield estimation methods the estimates of 10 kind of sediment rating curves were compared with actual loads of 5 stations in different climate zones of the country by using accuracy and precision index .the results show that in estimating long term mean load of the selected periods the Linear-MVUE sediment rating curve has relatively high accuracy and precision comparing other kinds of sediment rating curves. In average, the accuracy index of this method is about 1.23 that is reasonable among other methods. Since this kind of sediment, rating curve uses different data characteristics and information it could be recommend for application in sediment yield estimation within acceptable confidence limits.

In this paper, we propose a presmooth product-limit estimator to draw statistical inference on the unbiased distribution function representing the population of interest. The strong consistency of the estimator proposed is investigated. The finite sample performance of the proposed estimator is evaluated using simulation studies. It is observed that the proposed estimator exhibits greater efficiency in comparison with the alternative method in de Uñ a-Á lvarez (Test 11(1): 109– 125, 2002).

Power line signal are normally subjected to disturbance and noise which degrade the overall performance of power quality monitoring system. This paper proposes a modified approach for denoising by combining an algorithm known as Stein’s Unbiased Risk Estimator (SURE) algorithm incorporated with phaselet transform (PT). This algorithm is chosen particularly, as it not only performs denoising but also tends to optimally smooth the noisy signal. Since the algorithm is incorporated with phaselet, this leads to increase the coefficients obtained. Hence this method is found to be effective for application for denoising of power line signals. The different types of power quality signals simulated using the proposed method is found to be efficient and provide better results with increased Signal-to-Noise ratio (SNR) when compared with the results obtained by applying wavelet transform (WT).

Inversion of magnetic data is one of the important steps in the interpretation of practical magnetic data. The inversion result can be obtained by minimization of Tikhonov objective function. The determination of an optimal regularization parameter is highly important in magnetic data inversion. In this paper, an attempt has been made to use unbiased predictive risk estimator (UPRE) method in selecting the best regularization parameter for 3D constrained inversion of magnetic data using gradient projection reduced Newton (GPRN) algorithm. To achieve this goal, an algorithm has been developed to estimate this parameter. The validity of the proposed algorithm has been evaluated by magnetic data acquired from a synthetic model. The results have been compared with the results of generalized cross validation (GCV) method. The GCV method failed to estimate the regularization parameter, but the UPRE method could find the best regularization parameter. Then, the algorithm was used for inversion of real magnetic data obtained from Allah Abad iron deposit. The results of three-dimensional (3-D) inversion of magnetic data from this iron deposit show that the GPRN algorithm can provide an adequate estimate of magnetic susceptibility and geometry of subsurface structures of mineral deposits. A comparison of the inversion results with drilling data clearly indicate that the proposed algorithm can be used for 3-D inversion of magnetic data to estimate precisely the magnetic susceptibility and geometry of magnetized ore bodies.

Consider estimating the common meanè of two p-variate normal populations. A Best Linear Risk Unbiased Equivariant (BLRUE) estimator under LINEX loss function was proposed when the variances are known. Also a class of shrinkage estimators was studied.

Some examples of absurd uniformly minimum variance unbiased estimators are discussed. Two reasons, argued in the literature, for having such estimators are lack of enough information in the available data and property of unbiasedness. In this paper, accepting both of these views, we show that an appropriate choice of loss function using a general concept of unbiasedness leads to risk unbiased, admissible and reasonable estimators. For this we extend the Rao-Blackwell theorem using a new way of defining unbiased estimator.

Introduction:  The principal aim of the sheep industry worldwide is to produce high-quality meat. In addition to the meat, milk, and wool production are the economic traits in sheep breeding programs. Wool production is one of the most important economic characteristics of sheep with a complex physiological and biochemical process that is influenced by genetics, environment, and nutrition. Almost all Iranian sheep breeds are double-coated and produce carpet wool. Therefore, considering the role of wool on the country's economy, it is necessary to conduct a study to identify the genetic factors affecting this trait. Identifying the genomic regions under selection is effective in understanding the processes involved in the evolution of the genome and also in identifying the genomic regions involved in the emergence of economic traits. Selective signatures in the whole genome can help us to understand the mechanisms of selection and to identify the genomic regions that have been under natural or artificial selection for many years. Since Selective signatures are usually associated with major effect genes and important economic traits, they can provide suitable information sources to improve the performance of selection programs in the future. The objective of this study was to identify the genomic regions that have been under selection in skin and wool sheep breeds.Materials and methods: In the present study, Illumina ovine SNP600K BeadChip genomic arrays of 80 sheep from six breeds were used, three breeds were bred for their skin (Karakul, SiahKabud, and Gray Shiraz) and three breeds were bred for their wool (Sanjabi, Kermani and Baluchi). Unbiased methods of Weir and Cockerham’s FST (Theta) and hapFLK were used to detect the selection signatures. Also, to check the genes and QTLs in the selected regions, the Biomart database, OAR 3.1 version of the sheep genome, was used, and the function of the identified genes was analyzed through a wide search in different databases such as Genecards and OMIM. Finally, the list of genes related to the selected regions was reported. For this purpose, the chromosomal position of SNPs with high numerical values of theta and hapFLK, as well as the 250 kbp region around these markers, were further investigated. Then, the DAVID database online search was used to investigate the biological and functional processes of genes and to study the ontology. Finally, Cytoscape software was used to determine gene networks.Then, DAVID database online search was used to investigate the biological and functional processes of genes and to study the ontology.سپس از جستجوی آنلاین پایگاه داده DAVID برای بررسی فرآیندهای بیولوژیکی و عملکردی ژن ها و مطالعه هستی شناسی استفاده شد.Then, to investigate the biological and functional processes of genes and to study the ontology, DAVID database was used to search online.سپس برای بررسی فرآیندهای بیولوژیکی و عملکردی ژن ها و مطالعه هستی شناسی از پایگاه داده DAVID برای جستجوی آنلاین استفاده شد.Can't load full resultsTry againRetrying...Results and discussion: The results of the Theta analysis revealed 26 genomic regions on 1, 2, 6, 19, and 24 chromosomes, and the results of hapFLK revealed seven genomic regions on 6 and 19 chromosomes. Bioinformatics analysis demonstrated that some of these genomic regions overlapped with known genes related to pigment traits and characteristics of wool (KIT on chr 6, MITF on chr 19, IGSF10 on chr 1, PDGFRA on chr 6), muscles (MICALL2 on chr 24), vasodilation and immune response (P2RY on chr 1) and cancer (MIR339 on chr 24, ELFN1 on chr 24, MAD1L1 on chr 24, GPR87 on chr 1). The investigation of reported QTLs showed that these regions are related to QTLs of important economic traits, including traits related to meat, carcass, milk, body weight, bone density, and the total number of lambs born. Also, the analysis of Gene Ontology and Enriched pathway terms in regions under positive selection were related to the pathways involved in the differentiation of melanocytes and pigments, differentiation of stem cells, cellular processes, development of the immune system, blood system, reproductive and cellular processes. The results of the gene networks with the information obtained from Theta and hapFLK statistics showed that the genes identified were significantly active in the development and morphogenesis networks of the embryonic digestive tract, the networks related to pigment and melanocyte differentiation, and the networks related to Purine and G protein. However, to identify the exact function of the identified genes and QTLs, it is recommended to carry out more investigations.نتایج شبکه های ژنی با اطلاعات به دست آمده از آمار تتا و hapFLK نشان داد که ژن های شناسایی شده به طور معنی داری در شبکه های رشد و مورفوژنز دستگاه گوارش جنینی، شبکه های مربوط به تمایز رنگدانه و ملانوسیت و شبکه های مربوط بهThe results of the gene networks with the information obtained from theta and hapFLK statistics showed that the genes identified were significantly in the development and morphogenesis networks of the embryonic digestive system, the networks related to the differentiation of pigment and melanocytes and the networks related toنتایج شبکه های ژنی با اطلاعات به دست آمده از آمار تتا و hapFLK نشان داد که ژن های شناسایی شده به طور معنی داری در شبکه های رشد و مورفوژنز دستگاه گوارش جنینی، شبکه های مربوط به تمایز رنگدانه ها و ملانوسیت ها و شبکه های مربوط بهCan't load full resultsTry againRetrying...Conclusions: The results of the present study and the identified genomic regions can play an important role in the study of the effect of the selection on population differentiation in two sheep breeds that bred for skin and sheep production. Subsequently, this would direct us to identify the genomic regions associated with traits that differentiate these groups. However, these areas need to be confirmed in other independent studies with more samples. In general, the data of this research can be used in research related to genomic selection, design of mating systems, and additional reviews and evaluations to improve skin and wool production in sheep.