نتایج جستجو برای: factor matrix
تعداد نتایج: 1173306 فیلتر نتایج به سال:
abstract in this thesis at first we comput the determinant of hankel matrix with enteries a_k (x)=?_(m=0)^k??((2k+2-m)¦(k-m)) x^m ? by using a new operator, ? and by writing and solving differential equation of order two at points x=2 and x=-2 . also we show that this determinant under k-binomial transformation is invariant.
germinal matrix-intraventricular hemorrhage (ivh) is the most common variety of neonatal intracranial hemorrhage and is characteristics of the premature infant. the importance of the lesion relates not only to its high incidence but to their attendant complications (ic: hydrocephalus). brain sonography is the procedure of choice in diagnosis of germinal matrix- intraventricular hemorrhage and h...
objective: at present, growth factor-containing products such as enamel matrix derivatives, recombinant bone morphogenetic protein (rh-bmp), recombinant platelet derived growth factor and platelet rich plasma (prp) have gained increasing attention. prp is an autologous source of platelet growth factors used to enhance healing of soft and hard tissues. prp has gained popularity due to its autolo...
Gazestan magnetite-apatite deposit is located in Central Iran and Bafq region, which has been occurred in form of veins, veinlets, and small apatite lenses as well as magnetite in metasomatic rock types such as green chlorite-actinolite rock units. These rocks are situated in the carbonate-volcanic complex of Upper Precambrian-Lower Cambrian Rizo formation. In this study, staged factor analysis...
In this article, we study large-dimensional matrix factor models and estimate the loading matrices score by minimizing square loss function. Interestingly, resultant estimators coincide with Projected Estimators (PE) in Yu et al. which was proposed from perspective of simultaneous reduction dimensionality magnitudes idiosyncratic error matrix. other word, provide a least-square interpretation P...
This paper considers the estimation and inference of low-rank components in high-dimensional matrix-variate factor models, where each dimension matrix-variates ($p \times q$) is comparable to or greater than number observations ($T$). We propose an method called $\alpha$-PCA that preserves matrix structure aggregates mean contemporary covariance through a hyper-parameter $\alpha$. develop infer...
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