The human development index is an indicator to measure the quality of people's lives. If number increases, better There are many factors or variables that affect level index, ranging from economic issues, education, health and other factors. However, not all have a positive significant effect. Thus, this study aims determine significantly in South Sulawesi. method used principal component regre...

a spectrophotometric method for selective complexation reaction and simultaneous determination of mycophenolate mofetil (mpm), and mycophenolic acid (mpa) using three multivariate chemometric methods, i.e. partial least squares regression, principal component regression and principal component artificial neural networks, is proposed. the method is based on the complexation reaction of mpm and m...

This manuscript considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that they are clustered within groups or subjects. This data structure is increasingly common across scientific domains and is exemplified by our motivating example, in which binary curves indicating phys...

We solve principal component regression (PCR), up to a multiplicative accuracy 1+γ, by reducing the problem to Õ(γ−1) black-box calls of ridge regression. Therefore, our algorithm does not require any explicit construction of the top principal components, and is suitable for large-scale PCR instances. In contrast, previous result requires Õ(γ−2) such black-box calls. We obtain this result by de...

Network models are widely used to capture interactions among component of complex systems, such as social and biological. To understand their behavior, it is often necessary to analyze functionally related components of the system, corresponding to subsystems. Therefore, the analysis of subnetworks may provide additional insight into the behavior of the system, not evident from individual compo...

Inter-subject variability is a major hurdle for neuroimaging group-level inference, as it creates complex image patterns that are not captured by standard analysis models and jeopardizes the sensitivity of statistical procedures. A solution to this problem is to model random subjects effects by using the redundant information conveyed by multiple imaging contrasts. In this paper, we introduce a...

This manuscript considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that they are clustered within groups or subjects. This data structure is increasingly common across scientific domains and is exemplified by our motivating example, in which binary curves indicating phys...