In this thesis we look at the design and development of a Probabilistic Programming Language (PPL) in Julia named Turing and the challenges of implementing the Hamiltonian Monte Carlo (HMC) sampler inside the Turing framework. This dissertation starts with a review of three important fields behind the project, which are Bayesian inference, general inference algorithms and probabilistic programm...

We present our analysis of the nose-to-nose (ntn) method for use as an accurate sampler calibration method. The variations in the measurement of the sampler impulse response using the ntn method are described and the assertion that the kick-out pulse is identical to the sampler impulse response is assessed. Temperature effects on the ntn method are also examined. Finally, the effect of uncertai...

wind erosion is a significant problem on 20 million ha of iran, especially in central plains and coastal areas. winderosion samplers, meteorological equipments and measurement procedure have been developed over the last twocenturies to measure the particles moving across the field in modes of creep, saltation and suspension. in recentresearch as the first technical measurement in iran, wind ero...

Monitoring of harmful substances in an aquatic environment is based on spot sampling which is the only sampling technique accepted by environmental authorities in the European Union. Still the implementation of the European Union Water Framework Directive (WFD) requires novel sampling tools for monitoring priority pollutants since their concentrations in natural waters can often remain below th...

Spectroradiometric color measurements were performed at 26 regularly spaced points of a standard wine sampler into which 100 cc of wine were poured. Our goal is to describe the color changes occurring in this system, but not to propose a new method for wine-color measurement. Three samples of three different wines (red, rosé and white) were studied. From experimental measurements, lines of cons...

Among the computationally intensive methods for fitting complex multilevel models, the Gibbs sampler is especially popular owing to its simplicity and power to effectively generate samples from a high-dimensional probability distribution. The Gibbs sampler, however, is often justifiably criticized for its sometimes slow convergence, especially when it is used to fit highly structured complex mo...

For Bayesian inference on the mixture of factor analyzers, natural conjugate priors on the parameters are introduced, and then a Gibbs sampler that generates parameter samples following the posterior is constructed. In addition, a deterministic estimation algorithm is derived by taking modes instead of samples from the conditional posteriors used in the Gibbs sampler. This is regarded as a maxi...