Farmer Exchange Rate (FER) in Indonesia is very concerning. According to BPS data, there are various regions that experience increases and decreases every year. The goal of this paper predict the food crop sector using Principal Component Regression (PCR) since multicollinearity data. Therefore, with PCR method data based on 33 different provinces can determine supporting factors. model used he...

Methods 67 clinical and 24 environmental strains isolated from 2007 to 2010 were genotyped by PFGE, MLST and REP-PCR. Multiplex PCRs were performed for identification of the ompA, csuE and blaOXA-51like sequence type groups. The antimicrobial susceptibility was determined and the presence of carbapenemase-encoding genes was analysed by characterization of the blaOXA genes. Chlorine susceptibili...

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, intuitive accessible manner, basic principles underlying PCA its applications. Next, present a systematic, though no exclusive, survey some representative works illustrating poten...

Although fuzzy regression is widely employed to solve many problems in practice, what seems to be lacking is the problem of multicollinearity. In this paper, the fuzzy centers principal component analysis is proposed to first derive the fuzzy principal component scores. Then the fuzzy principal component regression (FPCR) is formed to overcome the problem of multicollinearity in the fuzzy regre...

Consider a regression problem where there is no labeled data and the only observations are the predictions fi(xj) of m experts fi over many samples xj . With no knowledge on the accuracy of the experts, is it still possible to accurately estimate the unknown responses yj? Can one still detect the least or most accurate experts? In this work we propose a framework to study these questions, based...

The objective was to evaluate correlations between suicide, homicide and socio-demographic variables by an ecological study. Mortality and socio-demographic data were collected from official records of the Ministry of Health and IBGE (2010), aggregated by state (27). The data were analyzed using correlation techniques, factor analysis, principal component analysis with a varimax rotation and mu...

We ran principal component regressions of growth and income on existing measures of institutions to assess which institutions are the most important for economic performance. We varied the sets of variables to search for robust effects of institutions. Our major finding is that broadly defined institutions of checks and balances limiting the power of the executive are the most robust institutio...

In the analysis of MDLAP, this paper creatively combines the mathematical optimization model of cost-based multiple targets distribution location problem into a logistics location selection decision model with a multiple influencing factors, then put forward the method of data standardization processing, entropy weight, the method of principal component analysis and mathematical expressions to ...