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Multiple myeloma is a hematological cancer of plasma B cells and remains incurable. Two major subtypes of myeloma, hyperdiploid MM (HMM) and non-hyperdiploid MM (NHMM), have distinct chromosomal alter...
Multiple myeloma is a hematological cancer of plasma B cells and remains incurable. Two major subtypes of myeloma, hyperdiploid MM (HMM) and non-hyperdiploid MM (NHMM), have distinct chromosomal alter...
We propose here a novel method of factor profiling (FP) for ultra high dimen-sional variable selection. The new method assumes that the correlation structure of the high dimensional data can be well r...
We study a factor model for the correlation matrix $\Sigma\in\RR^{d\times d}$ of an elliptical copula. The correlations are connected to Kendall's tau and a natural estimation procedure is to plug-in ...
In this short paper, we introduce a mixture of skew-t factor analyzers as well as a family of mixture models based thereon. The mixture of skew-t distributions model that we use arises as a limiting c...
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Fact...
We develop a new model and algorithms for machine learning-based learning analytics, which estimate a learner's knowledge of the concepts underlying a domain, and content analytics, which estimate the...
In a recent series of high impact public health publications, the c-index was used as measure of prediction to assess the public health relevance of a risk factor. I demonstrate that the c-index is an...
In model-based clustering and classification, the cluster-weighted model constitutes a convenient approach when the random vector of interest constitutes a response variable Y and a set p of explanato...
We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis ...
The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon...
Our article considers a regression model with observed factors. The observed factors have a flexible stochastic volatility structure that has separate dynamics for the volatilities and the correlation...
We examine a general multi-factor model for commodity spot prices and futures valuation. We extend the multi-factor long-short model in [1] and [2] in two important aspects: firstly we allow for both...
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting spar...
We present a novel factor analysis method that can be applied to the discovery of common factors shared among trajectories in multivariate time series data. These factors satisfy a precedence-ordering...

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