A Poisson Ridge Regression Estimator

The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression estimator (PRR) as a remedy to the problem of instability of the traditional ML method. To investigate the performance of the PRR and the traditional ML approaches for estimating the parameters of the Poisson regression model, we calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR method outperforms the traditional ML estimator in all of the different situations evaluated in this paper.Poisson regression; maximum likelihood; ridge regression; MSE; Monte Carlo simulations; Multicollinearity

Performance of Some Ridge Parameters for Probit Regression: with Application on Swedish Job Search Data

In ridge regression the estimation of the ridge parameter is an important issue. This paper generalizes some methods for estimating the ridge parameter for probit ridge regression (PRR) model based on the work of Kibria et al. (2011). The performance of these new estimators are judged by calculating the mean square error (MSE) using Monte Carlo simulations. In the design of the experiment we chose to vary the sample size and the number of regressors. Furthermore, we generate explanatory variables that are linear combinations of other regressors, which is a common situation in economics. In an empirical application regarding Swedish job search data we also illustrate the benefits of the new method.probit regression; maximum likelihood; multicollinearity; ridge regression; MSE; job search

A New Ridge Regression Causality Test in the Presence of Multicollinearity

This paper analyzes and compares the properties of the most commonly applied versions of the Granger causality (GC) test to a new ridge regression GC test (RRGC), in the presence of multicollinearity. The investigation has been carried out using Monte Carlo simulations. A large number of models have been investigated where the number of observations, strength of collinearity, and data generating processes have been varied. For each model we have performed 10000 replications and studied seven different versions of the test. The main conclusion from our study is that the traditional OLS version of the GC test over-rejects the true null hypothesis when there are relatively high (but empirically common levels of) multicollinearity, while it is established that the new RRGC test will remedy or substantially decrease this problem.Granger causality test; multicollinearity; ridge parameters; size and power

Comparative study on the effectiveness of building maintenance scheduling between two multipurpose hall buildings

Buildings maintenance is very important for the building and building occupants. Maintenance is a service to make sure the performance of the building in good condition throughout its design life. It is very much needed so we can have very good environment that can help us do our work peacefully. Occupants demand to have priority in terms of comfort of ability to use and utilise the facilities and services as it must be fit for purpose of the user. Work productivity of workers may be demotivated and interrupted due to poor building facilities conditions. In order to prevent that, we have to make sure the building maintenance scheduling are well prepared and followed. This study is about comparative study on the effectiveness of building maintenance scheduling between two multipurpose hall buildings. The objectives of the case study are to investigate the procedure of building maintenance scheduling for the buildings, compare the maintenance scheduling approach between the two multipurpose hall buildings and suggest the best method to practice in the development of building maintenance. This investigation will be carried out through field study and interview from both building. At the end of this study, the data for analysis from the interview have been gathered and it shows that both building are using the same maintenance approaches. Discussion has been explained to provide the comparison for the effectiveness of building maintenance scheduling for both building. Both buildings had made improvement in the building to overcome the building defects and increase the building performance. The buildings have been properly maintain in order to keep it well perform. Some recommendations have been suggested for the future used in having effective building maintenance scheduling. The results from this study are the effectiveness of building maintenance scheduling for both multipurpose buildings have been properly studied and investigated

Modified Ridge Parameters for Seemingly Unrelated Regression Model

In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge RMSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high the unbiased SUR, estimator produces a smaller TMSEs.Multicollinearity; modified SUR ridge regression; Monte Carlo simulations; TMSE