Methods of incorporating a ridge type of regularization into partial redundancy analysis (PRA), constrained redundancy analysis (CRA), and partial and constrained redundancy analysis (PCRA) were discussed. The usefulness of ridge estimation in reducing MSE (mean square error) has been recognized in multiple regression analysis for some time, especially when predictor variables are nearly collin...

We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the...

Ridge orientation is one of the fundamental features of a fingerprint image. Orientation estimation serves for feature extraction and matching and is the base of fingerprint recognition. Most existing orientation estimation methods are based on the characteristic of pixel intensity in a block. This paper uses neural network to learn the ridge orientation. The trained network has the property of...

The paper aims to investigate the improvement that Ridge regression brings to the commercial real estate index estimation. The MIT transaction based index extends the use of the last model by Fisher, Gatzlaff, Geltner and Haurin (2003.) They address the sample selection bias and the noise effect of the transaction prices in small sample. To correct sample selection bias, MIT transaction index u...

In this paper, we discuss a unified theory for and performance evaluation of the ridge direction estimation through the minimization of the integral of the second directional derivative of the gray-level intensity function. The primary emphasis of this paper is on the ridge orientation estimation. The subsequent ridge detection can be performed using the traditional methods of using the zero cr...

The generalized density is a product of a density function and a weight function. For example, the average local brightness of an astronomical image is the probability of finding a galaxy times the mean brightness of the galaxy. We propose a method for studying the geometric structure of generalized densities. In particular, we show how to find the modes and ridges of a generalized density func...

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the Lagrangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the crossvalidation procedure for selecting the o...

Background: In forensic sciences, the nature and variability of configurations of epidermal ridge minutiae has practically been explored in the evaluation and comparison of fingerprints, including partial fingerprints. The objectives of the present study were to determine the potential of fingerprint minutiae (level two features) in estimation of sex using likelihood ratio and posterior probabi...

Anomalies persist in the foundations of ridge regression as set forth in Hoerl and Kennard (1970) and subsequently. Conventional ridge estimators and their properties do not follow on constraining lengths of solution vectors using LaGrange’s method, as claimed. Estimators so constrained have singular distributions; the proposed solutions are not necessarily minimizing; and heretofore undiscover...