Search results for " Sampling"

Lattices and dual lattices in optimal experimental design for Fourier models

1998

Number-theoretic lattices, used in integration theory, are studied from the viewpoint of the design and analysis of experiments. For certain Fourier regression models lattices are optimal as experimental designs because they produce orthogonal information matrices. When the Fourier model is restricted, that is a special subset of the full factorial (cross-spectral) model is used, there is a difficult inversion problem to find generators for an optimal design for the given model. Asymptotic results are derived for certain models as the dimension of the space goes to infinity. These can be thought of as a complexity theory connecting designs and models or as special type of Nyquist sampling t…

Deepening Inside the Pictorial Layers of Etruscan Sarcophagus of Hasti Afunei: An Innovative Micro-Sampling Technique for Raman/SERS Analyses

2019

The Hasti Afunei sarcophagus is a large Etruscan urn, made up of two chalky alabaster monoliths. Dated from the last quarter of the third century BC, it was found in 1826 in the small town of Chiusi (Tuscany- Il Colle place) by a landowner, Pietro Bonci Casuccini, who made it part of his private collection. The noble owner&rsquo

INVESTIGATING MARKET POTENTIAL FOR STREAMING SUBSCRIPTION MODEL IN EMERGING ECONOMIES : A CASE OF NIGERIA

2018

Master's thesis Music management MU501 - University of Agder 2018 Building on two marketing theories: the product and marketing concept, this study conceptualizes how music sampling, consumers’ income and attitude affect streaming subscription in Nigeria. The aim is to test whether efficient market for streaming subscription could be developed in emerging economies and contribute to growth in the world digital music markets. The study used a binomial logistic regression to analyse 230 observations obtained from a survey data to estimate a conceptual framework. Results show that music sampling positively affect streaming subscription. Conversely, consumers’ income and attitude are both not s…

Viaggi multi destinazione e turismo sommerso: l'indagine sul turismo incoming in Sicilia

2013

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

2020

We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelisation and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the sug…

Intra-urban residential differentiation in the post-Soviet city: the case of Riga, Latvia

2014

Cities in many Central and Eastern European (CEE) countries have transformed rapidly since the political and socio-economic restructuring started in the early 1990s. Economi reforms, growing income inequalities, changes in housing system and selective residential mobility are resulting in increasing socio-spatial differentiation among urban neighbourhoods also in Riga. In addition, litt le is known about the ethnic dimension of intra-urban residential differentiation, despite the existence of sizeable minority populations. The focus on ethnicity is important, since Riga is the only capital city in the Baltic States where the ethnic majority is outnumbered by the non-Latvian minority. This p…

Ambulatory assessment as a means of longitudinal phenotypes characterization in psychiatric disorders

2014

Abstract Ambulatory Assessment (AA) comprises the use of in-field methods to assess individuals’ behavior, physiology, and the experience as they unfold in naturalistic settings. We propose that AA is favorable for the investigation of gene–environment interactions and for the search for endophenotypes, being able to assess the experienced environment and to track basic regulatory processes, such as stress reactivity, affective instability, and reward experience, which are potential common factors that underlie psychiatric disorders. In this article, we (a) first describe briefly the rationale of AA and summarize the key advantages of the approach, (b) highlight within-subject regulatory pr…

AN EMPIRICAL STUDY OF LATVIAN CONSUMER’S ATTITUDES AND PERCEPTIONS TOWARDS GENETICALLY MODIFIED ORGANISMS

2016

Genetic modification and genetically modified organisms (GMO) remains a controversial issue. Latvian consumers’ attitude towards genetic modification and GMO have been characterized as negative using Eurobarometer data, but so far no specific investigation of Latvian consumers has been done in this field. The aim of this study was to analyse Latvian consumers’ attitude towards genetic modification and GMO, the subjective and objective knowledge about this questions and acceptability of use of GMO in different application areas. Main task in frame of this research is to summarize different literature and data available to outline some of factors that influence attitudes towards GMO: mainly p…

Group Metropolis Sampling

2017

Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes…

Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation

2019

The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…