Sample size determination for kernel regression estimation using sequential fixed-width confidence bands

We consider a random design model based on independent and identically distributed pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths. The sample size was optimized using the purely and two-stage sequential procedures together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confi dence bands based on the local linear estimator have the better performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.

An integration of attachment theory and reinforcement sensitivity theory

This thesis examined how relationship experiences shape people's sensitivity to detect threat and reward in romantic relationships and substance use scenarios. Findings indicated that anxious individuals experienced difficulty in distinguishing between threat and reward. In contrast, avoidant individuals were quick to detect threat either fleeing or confronting the problem aggressively.

Forces measured between latex spheres in aqueous electrolyte : Non-DLVO behavior and sensitivity to dissolved gas

An atomic force microscope was used to measure the forces acting between two polystyrene latex spheres in aqueous media. The results show an electrostatic repulsion at large separations which is overtaken by an attractive “hook” that pulls the two spheres into contact from a considerable range (20−400 nm), much larger than could be expected for a van der Waals attraction. The range of operation of this attraction varies from one experiment to another and is not correlated with electrolyte concentration. However, the range is found to decrease significantly when the level of dissolved gas in the water is reduced.

Software reliability growth models based on local polynomial modeling with kernel smoothing

Software reliability growth models (SRGMs) are extensively employed in software engineering to assess the reliability of software before their release for operational use. These models are usually parametric functions obtained by statistically fitting parametric curves, using Maximum Likelihood estimation or Least–squared method, to the plots of the cumulative number of failures observed N(t) against a period of systematic testing time t. Since the 1970s, a very large number of SRGMs have been proposed in the reliability and software engineering literature and these are often very complex, reflecting the involved testing regime that often took place during the software development process. In this paper we extend some of our previous work by adopting a nonparametric approach to SRGM modeling based on local polynomial modeling with kernel smoothing. These models require very few assumptions, thereby facilitating the estimation process and also rendering them more relevant under a wide variety of situations. Finally, we provide numerical examples where these models will be evaluated and compared.

Climate change sensitivity of comfort and energy performance criteria for offices

The climate change scenarios of the Intergovernmental Panel on Climate Change (IPCC) predict a significant increase in temperatures over the next decades. Architecture and building occupants have to respond to this change, but little information is currently available in how far the predicted changes are likely to affect comfort and energy performance in buildings. This study therefore investigates the climate change sensitivity of the following parameters: adaptive thermal comfort according to Ashrae Standard 55 and EN 15251, energy consumption, heating and cooling loads, and length of heating and cooling periods. The study is based on parametric simulations of typical office room configurations in the context of Athens, Greece. They refer to different building design priorities and account for different occupant behaviour by using an ideal and worst case scenario. To evaluate the impact of the climate change, simulations are compared based on a common standard weather data set for Athens, and a generated climate change data set for the IPCC A2 scenario. The results show a significant impact of the climate change on all investigated parameters. They also indicate that in this context the optimisation of comfort and energy performance is likely to be related to finding the best possible balance between building (design) and occupant behaviour and other contextual influences, rather than a straightforward optimisation of separated single parameters.