AbstractWe report a matrix expression for the covariance matrix of MLEs of factor loadings in factor analysis. We then derive the analytical formula for covariance matrix of the covariance estimators of MLEs of factor loadings by obtaining the matrix of partial derivatives, which maps the differential of sample covariance matrix (in vector form) into the differential of the covariance estimators
This dissertation studies time-varying high-dimensional covariance matrix estimations. I propose two...
For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an ob...
summary:The author shows that a decomposition of a covariance matrix $\bold{\sum = AA'}$ implies the...
We report a matrix expression for the covariance matrix of MLEs of factor loadings in factor analysi...
AbstractWe report a matrix expression for the covariance matrix of MLEs of factor loadings in factor...
AbstractSuppose that random factor models with k factors are assumed to hold for m, p-variate popula...
AbstractThis paper is concerned with the asymptotic covariance matrix (ACM) of maximum-likelihood es...
This thesis considers two problems related to high-dimensional covariance matrices, namely, covarian...
It is known that the principal component estimates of the factors and the loadings are rotations of ...
AbstractA general matrix expression for the asymptotic covariance matrix of correlation coefficients...
AbstractWe consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. ...
In this paper a martingale approximation is used to derive the limiting distribution of simple posit...
AbstractThe asymptotic covariance matrix of the sample correlation matrix is derived in matrix form ...
This paper proposes to estimate the covariance matrix of stock returns by an optimally weighted aver...
We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Stat...
This dissertation studies time-varying high-dimensional covariance matrix estimations. I propose two...
For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an ob...
summary:The author shows that a decomposition of a covariance matrix $\bold{\sum = AA'}$ implies the...
We report a matrix expression for the covariance matrix of MLEs of factor loadings in factor analysi...
AbstractWe report a matrix expression for the covariance matrix of MLEs of factor loadings in factor...
AbstractSuppose that random factor models with k factors are assumed to hold for m, p-variate popula...
AbstractThis paper is concerned with the asymptotic covariance matrix (ACM) of maximum-likelihood es...
This thesis considers two problems related to high-dimensional covariance matrices, namely, covarian...
It is known that the principal component estimates of the factors and the loadings are rotations of ...
AbstractA general matrix expression for the asymptotic covariance matrix of correlation coefficients...
AbstractWe consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. ...
In this paper a martingale approximation is used to derive the limiting distribution of simple posit...
AbstractThe asymptotic covariance matrix of the sample correlation matrix is derived in matrix form ...
This paper proposes to estimate the covariance matrix of stock returns by an optimally weighted aver...
We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Stat...
This dissertation studies time-varying high-dimensional covariance matrix estimations. I propose two...
For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an ob...
summary:The author shows that a decomposition of a covariance matrix $\bold{\sum = AA'}$ implies the...