New issue New issue Closed Closed [Bug]: Multiple regression SEM - Error: lavaan->lav_samplestats_icov (): sample covariance matrix is not positive-definite #3117 Assignees Labels Module: jaspSemOS: ...

For example, suppose a risk manager wants to calculate the value at risk using the parametric method for a one-day time horizon. The weight of the first asset is 40%, and the weight of the second ...

Shrinkage regularization is an effective strategy to estimate the covariance matrix of multi-variate random vector in small sample scenarios. The purpose of this paper is to propose improved linear ...

This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of ...

This study contributes to the ongoing discussion by investigating whether risk factor disclosures contain valuable information that can be used to improve the estimation of the covariance matrix of ...

covMarket: Linear shrinkage towards a one-factor market model, where the factor is defined as the cross-sectional average of all the random variables; thanks to the idiosyncratic volatility of the ...

More subtle, but significant changes of correlation can also be observed between single stocks and/or between sectors in the stock market. For example, a downward move of the S&P 500 leads to an ...

As training samples are not always target-free in space-time processing for airborne radar, the traditional methods usually use the sample covariance matrix (SCM) as the test covariance matrix (TCM) ...