intensity is one of the useful information in extract earthquake analyzing of a region; then, preparing a complete dataset of them is necessary for each region. one of the best intensity information of the most historical and several instrumental earthquakes in iran (from year 658 to 1979) was reported in an intensity scale with five degrees. there are also several earthquakes with reported int...

In the linear regression setting, we propose a general framework, termed weighted orthogonal components (WOCR), which encompasses many known methods as special cases, including ridge and principal regression. WOCR makes use of monotonicity inherent in to parameterize weight function. The formulation allows for efficient determination tuning parameters hence is computationally advantageous. More...

Orthogonal Distance Regresson (ODR) is the name given to the computational problem associated with finding the maximum likelihood estimators of parameters in measurement error models in the case of normally distributed errors. We examine the stable and efficient algorithm of Boggs, Byrd and Schnabel (SIAM J. Sci. Stat. Comput., 8 (1987), pp. 1052– 1078) for finding the solution of this problem ...

Assessing the linear relationship between a set of continuous predictors and a continuous response is a well studied problem in statistics and is applied in many data mining situations. L2 based methods such as ordinary least squares and principal components regression can be used to determine this relationship. However, both of these methods become impaired when multicollinearity is present. T...

Linear functional relationships are intended to be symmetric and therefore cannot generally accurately estimated using ordinary least squares regression equations. Orthogonal (OR) models allow for errors in both Y X can provide estimates of these relationships. The most well-established OR model, the errors-in-variables (EIV) assumes that observed scatter around line is due entirely measurement...