Infrence for non-negative autoregressive schemes

The object of this paper is the statistical analysis of Several Closely related models arising in water quality analysis. In particular, concern is with the autoregressive scheme X_r = ρX_r?1 + Y_r where 0 < ρ < 1 and Y's are i.i.d, and non-negative. The estimation and testing problem is considered for three parametric models - Gaussian, uniform and exponential - as well as for the nonparametric case where it is assumed that the Y's have a positive continuous distribution.     

Approximate Formulae for Bias and Variance of Ratios

Rao ([1], p. 475, equation 8c.6.10) considers a certain minimization problem in which one is required to minimize a sum of quadratic forms subjected to certain linear restrictions. The proof given by Rao, although elegant, is involved and complicated as he uses N dimensional geometric and regression theory arguments. Perhaps, an alternative simpler and straightforward algebraic proof of this minimization problem might be of interest.     

Using regression mixture models with non-normal data: examining an ordered polytomous approach

Mild to moderate skew in errors can substantially impact regression mixture model results; one approach for overcoming this includes transforming the outcome into an ordered categorical variable and using a polytomous regression mixture model. This is effective for retaining differential effects in the population; however, bias in parameter estimates and model fit warrant further examination of this approach at higher levels of skew. The current study used Monte Carlo simulations; 3000 observations were drawn from each of two subpopulations differing in the effect of X on Y. Five hundred simulations were performed in each of the 10 scenarios varying in levels of skew in one or both classes. Model comparison criteria supported the accurate two-class model, preserving the differential effects, while parameter estimates were notably biased. The appropriate number of effects can be captured with this approach but we suggest caution when interpreting the magnitude of the effects.     

From design to operations: a process management life-cycle performance measurement system for Public-Private Partnerships

Public–Private Partnerships (PPPs) have become a critical vehicle for delivering infrastructure worldwide. Yet, the use of such a procurement strategy has received considerable criticism, as they have been prone to experiencing time/cost overruns and during their operation poorly managed. A key issue contributing to the poor performance of PPPs is the paucity of an effective and comprehensive performance measurement system. There has been a tendency for the performance of PPPs to be measured based on their ex-post criteria of time, cost and quality. Such criteria do not accommodate the complexities and lifecycle of an asset. In addressing this problem, the methodology of sequential triangulation is used to develop and examine the effectiveness of a ‘Process Management Life Cycle Performance Measurement System’. The research provides public authorities and private-sector entities embarking on PPPs with a robust mechanism to effectively measure, control and manage their projects’ life cycle performances, ensuring the assets are ‘future proofed’.     

360 Video: A prototyping process for developing virtual reality interventions

Abstract

Virtual reality (VR) has emerged as a promising technological intervention for anxiety disorders. However, there are no existing standards and best practices to evaluate the effectiveness of environments to achieve their intervention goals. The purpose of this study was to develop a VR intervention for student veterans with social anxiety disorder and test feasibility utilizing a three-stage development model. The development of a therapeutic VR environment may benefit from an interdisciplinary collaboration of researchers from various fields of study. Utilizing three stages of prototyping with two virtual reality platforms, fully immersive video (n?=?6) and three-dimensional (3-D) immersive virtual reality (n?=?8), the research team designed an intervention for student veterans with social anxiety disorder, testing bio-reactivity of participants. Results of prototyping include user feedback validating increased stress levels and increased bio-reactivity specifically in galvanic skin response and heart rate elevation. Implications include the use of 360° video for prototyping 3-D virtual reality interventions.