The penalized profile sampler for semiparametric inference is an extension of the profile sampler method [9] obtained by profiling a penalized log-likelihood. The idea is to base inference on the posterior distribution obtained by multiplying a profiled penalized log-likelihood by a prior for the parametric component, where the profiling and penalization are applied to the nuisance parameter. B...

Quantifying the errors introduced by signal sampler imperfections is of interest to people who are doing frequency domain measurements. The phase-distortion introduced by the sampler is hard to quantify and is usually neglected. In this article upper bounds for this phase-distortion error are derived which are based upon simple assumptions, namely that the sampler weighting function is strictly...

3⁄4We measured a signal current waveform by using a high-Tc superconductor (HTS) sampler with a 1-ps delay between every sampling point. The maximum time differential obtained in the measured waveform was 12 mA/ps with 2.5-mA current sensitivity at 25 K. This result guarantees that the sampler is able to measure current waveforms correctly when their maximum time differential is less than 12 mA...

Six inhalable aerosol samplers were evaluated experimentally as area samplers using monodisperse solid particles with aerodynamic diameters ranging from 5 to 68 microm. Sampler performance and inside particle loss at two test wind speeds (0.55 and 1.1 m/sec) and three wind orientations (0, 90, and 180 degrees) were investigated. The six inhalable aerosol samplers tested were a RespiCon, an Inst...

A modified large-volume sampler was demonstrated to be an efficient device for the collection of mono-disperse aerosols of rhodamine B and poly-disperse aerosols of bacterial cells. Absolute efficiency for collection of rhodamine B varied from 100% with 5-mum particles to about 70% with 0.5-mum particles. The sampler concentrated the particles from 950 liters of air into a flow of between 1 and...

Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive a...

A fundamental task in machine learning and related fields is to perform inference on probabilistic graphical models. Since exact inference takes exponential time in general, a variety of approximate methods are used. Gibbs sampling is one of the most accurate approaches and provides unbiased samples from the posterior but it has historically been too expensive for large models. In this paper, w...

To obtain specimens from marine environment, water sampling devices such as Nansen's sampler and sediment sampling device such as a gravity-core sampler are used for geological or ecological examinations in oceanic or aquatic fields. Those samplers are able tocollect a reasonable amount of specimens for the above studies. These devices are all considerably heavy and operated by means of a rope ...

For studies of the biological effects of bioaerosols, large samples are necessary. To be able to sample enough material and to cover the variations in aerosol content during and between working days, a long sampling time is necessary. Recently, a high-volume transportable electrostatic field sampler for collection of fine particles has been described. The aim of this study was to investigate wh...