This paper compares ordinary least squares (OLS), weighted least squares (WLS), and adaptive least squares (ALS) by means of a Monte Carlo study and an application to two empirical data sets. Overall, ALS emerges as the winner: It achieves most or even all of the efficiency gains of WLS over OLS when WLS outperforms OLS, but it only has very limited downside risk compared to OLS when OLS outper...

A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between inand output can he approximated, even when the structure of this relation is unknown beforehand. This method can adapt its structure on-line while it preserves information offered by previous samples, making it applicable in a control setting. This method has b...

This contribution presents a simple, attractive, and exible formulation for the weighted total least squares (WTLS) problem. It is simple because it is based on the well-known standard least squares theory; it is attractive because it allows one to directly use the existing body of knowledge of the least squares theory; and it is exible because it can be used to a broad eld of applications in t...

Updating a linear least squares solution can be critical for near real-time signalprocessing applications. The Greville algorithm proposes simple formula updating the pseudoinverse of matrix A $\in$ R nxm with rank r. In this paper, we explicitly derive similar by maintaining general factorization, which call rank-Greville. Based on formula, implemented recursive exploiting rank-deficiency A, a...

The hyperspectral image compression scheme is a trade-off between the limited hardware resources of on-board platform and ever-growing resolution optical instruments. Predictive coding attracts researchers due to its low computational complexity moderate memory requirements. We propose near-lossless prediction-based that removes spatial spectral redundant information, thereby significantly redu...

Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first de...