Search results for "Markov"
showing 10 items of 628 documents
Forecasting Hepatitis C liver disease burden on real-life data. Does the hidden iceberg matter to reach the elimination goals?
2018
Abstract Background & Aims Advances in direct‐acting antiviral treatment of HCV have reinvigorated public health initiatives aimed at identifying affected individuals. We evaluated the possible impact of only diagnosed and linked‐to‐care individuals on overall HCV burden estimates and identified a possible strategy to achieve the WHO targets by 2030. Methods Using a modelling approach grounded in Italian real‐life data of diagnosed and treated patients, different linkage‐to‐care scenarios were built to evaluate potential strategies in achieving the HCV elimination goals. Results Under the 40% linked‐to‐care scenario, viraemic burden would decline (60%); however, eligible patients to treat w…
CArDIS : A Swedish Historical Handwritten Character and Word Dataset
2022
This paper introduces a new publicly available image-based Swedish historical handwritten character and word dataset named Character Arkiv Digital Sweden (CArDIS) (https://cardisdataset.github.io/CARDIS/). The samples in CArDIS are collected from 64, 084 Swedish historical documents written by several anonymous priests between 1800 and 1900. The dataset contains 116, 000 Swedish alphabet images in RGB color space with 29 classes, whereas the word dataset contains 30, 000 image samples of ten popular Swedish names as well as 1, 000 region names in Sweden. To examine the performance of different machine learning classifiers on CArDIS dataset, three different experiments are conducted. In the …
Helikobaktērijas eradikācijas izmaksu efektivitātes novērtējums Latvijas sabiedrībā
2019
Helikobaktērija (Helicobacter Pylori – no latīņu val.) ir izplatīta infekcioza slimība, kas paaugstina dažādu kuņģa slimību veidošanās risku. Saslimstība veicina ārstniecības izmaksu paaugstināšanos, indivīda darba nespēju, kā arī citus ekonomiskos zaudējumus. Baktērijas ārstniecībai populācijas līmenī ir potenciāls samazināt tās izplatību un paaugstināto saslimšanas risku ar dažādām kuņģa slimībām. Tomēr ārstniecība saistās ar augstām īstenošanas izmaksām un nav skaidrības vai Latvijā tā būtu izmaksu efektīva. Darba mērķis ir noskaidrot vai potenciāli pastāv izmaksu efektīva helikobaktērijas eradikācijas intervences stratēģija Latvijas sabiedrībā. Iegūtie rezultāti liecina, ka eradikācijas…
First hitting time for a diffusion
2021
In this thesis, we focus our attention on the generation of the first exit time or the first passage time for diffusions in a one-dimensional context.In the first chapter, we present already well-known methods in order to generate such random variables. We particularly introduce the WOMS algorithm. This algorithm permits the generation of an approximation of the time needed by the Brownian motion in order to exit from a given interval.In the second and third chapters, we explain how to extend the previous algorithm in order to deal with diffusions strongly linked to the one-dimensional Brownian motion. We first consider the Ornstein-Uhlenbeck process, and then we consider a wide class of di…
Mapping discounted and undiscounted Markov Decision Problems onto Hopfield neural networks
1995
This paper presents a framework for mapping the value-iteration and related successive approximation methods for Markov Decision Problems onto Hopfield neural networks, for both discounted and undiscounted versions of the finite state and action spaces. We analyse the asymptotic behaviour of the control sets and we give some estimates on the convergence rate for the value-iteration scheme. We relate the convergence properties on an energy function which represents the key point in mapping Markov Decision Problems onto Hopfield networks. Finally, an application from queueing systems in communication networks is taken into consideration and the results of computer simulation of Hopfield netwo…
Sequential Monte Carlo Methods in Random Intercept Models for Longitudinal Data
2017
Longitudinal modelling is common in the field of Biostatistical research. In some studies, it becomes mandatory to update posterior distributions based on new data in order to perform inferential process on-line. In such situations, the use of posterior distribution as the prior distribution in the new application of the Bayes’ theorem is sensible. However, the analytic form of the posterior distribution is not always available and we only have an approximated sample of it, thus making the process “not-so-easy”. Equivalent inferences could be obtained through a Bayesian inferential process based on the set that integrates the old and new data. Nevertheless, this is not always a real alterna…
Is land-use change a cause of loss of pedodiversity? The case of the Mazzarrone study area, Sicily
2011
Anthropogenic soils created ex novo by land-us e change in large scale farming are, from a pedogenetic point of view, catastrophic events that bring the soils to time zero and change the natural pattern of the soilscape, remarkably, in some cases. The qu antitative aspects of pedodiversity of a soilsc ape in South-East Sicily, where some types of soils, in recent decades, have suffered a consistent reduction due to the transformations by large scale farming, are considered. The evolution of pedodiversity over a 53-year period (1955 to 2008 ) is examined using a dedicated statistical method and a space – time model based on Markov analysis and cellular autom ata in order to predict the evolu…
A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from Isotope Tracer Addition Experiments
2020
Understanding how nutrients flow through food webs is central in ecosystem ecology. Tracer addition experiments are powerful tools to reconstruct nutrient flows by adding an isotopically enriched element into an ecosystem and tracking its fate through time. Historically, the design and analysis of tracer studies have varied widely, ranging from descriptive studies to modeling approaches of varying complexity. Increasingly, isotope tracer data are being used to compare ecosystems and analyze experimental manipulations. Currently, a formal statistical framework for analyzing such experiments is lacking, making it impossible to calculate the estimation errors associated with the model fit, the…
Multi-year drought frequency analysis at multiple sites by operational hydrology - A comparison of methods
2006
Abstract This paper compares two generators of yearly water availabilities from sources located at multiple sites with regard to their ability to reproduce the characteristics of historical critical periods and to provide reliable results in terms of the return period of critical sequences of different length. The two models are a novel multi-site Markov mixture model explicitly accounting for drought occurrences and a multivariate ARMA. In the case of the multisite Markov mixture model parameter estimation is limited to a search in the parameter space guided by the value of parameter λ to show the sensitivity of the model to this parameter. Application to two of the longest time series of …
Towards Model-Based Reinforcement Learning for Industry-Near Environments
2019
Deep reinforcement learning has over the past few years shown great potential in learning near-optimal control in complex simulated environments with little visible information. Rainbow (Q-Learning) and PPO (Policy Optimisation) have shown outstanding performance in a variety of tasks, including Atari 2600, MuJoCo, and Roboschool test suite. Although these algorithms are fundamentally different, both suffer from high variance, low sample efficiency, and hyperparameter sensitivity that, in practice, make these algorithms a no-go for critical operations in the industry.