background: the primary objective of this study was to determine the association between risk factors and the prevalence of musculoskeletal disorder (msd) among auto repair mechanics in klang valley, malaysia. methods: overall, 191 mechanics from eight auto repair centers in klang valley, malaysia were stratified sampling as participants of this study. a modified version of the general standard...

This paper develops a framework for stress-testing the credit risk of Chinese commercial banks to macroeconomic shocks. Using data over the period 1985-2008, this study establishes a vector auto-regression (VAR) model to describe the links between default rate and macroeconomic factors, and then designs three stress scenarios to implement the stress testing by Monte Carlo simulation. As a resul...

I introduce inside money and serially correlated supply shocks to the Uncertain and Sequential Trading (UST) monetary model and test its implications using a vector auto regression impulse response analysis on post-war US data. I find that (a) The importance of money in predicting output is substantially reduced once the stock of inventories is added to the VAR system and (b) Shocks to inventor...

abstract exchange rate volatility is one of the effective and ambiguous factors in agricultural products export. regarding the importance of agricultural trade, to avoid single-product economy, the main aim of this study is to investigate the impact of exchange rate volatility on the pistachio export of iran during 1338-1386. for this purpose, exchange rate volatility index was estimated using ...

We propose a novel idea of regression – balancing the distances from a regression function to all examples. We created a method, called balanced support vector regression (balanced SVR) in which we incorporated this idea to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem. We implemented our method for two versions of SVR: ε-insensitive support ve...

We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y , taking values in R given covariates Z = z, taking values in R, is a map u 7→ QY |Z(u, z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U follows a reference non-atomic distr...

In this letter, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal scales. Both approaches guarantee that the thresholds are properly ordered at the optimal solution. The size of these optimization problems is linear in the number of training samples. The sequential minimal optimizat...

We show that the Bayesian evidence framework can be applied to both-support vector regression (-SVR) and-support vector regression (-SVR) algorithms. Standard SVR training can be regarded as performing level one inference of the evidence framework, while levels two and three allow automatic adjustments of the regularization and kernel parameters respectively, without the need of a validation set.

Extreme Support Vector Machine (ESVM), a variant of ELM, is a nonlinear SVM algorithm based on regularized least squares optimization. In this chapter, a regression algorithm, Extreme Support Vector Regression (ESVR), is proposed based on ESVM. Experiments show that, ESVR has a better generalization ability than the traditional ELM.Furthermore, ESVMcan reach comparable accuracy as SVR and LS-SV...