Price forecasting in the day-ahead Iberian electricity market using a conjectural variations Arima model

Price forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naive and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naive and that it performs slightly better than the direct price forecast.

Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.

Avaliação dos parâmetros do índice de qualidade de água segundo o modelo ARIMA

Time series tendencies are an important tool for different sectors such as the scientific community, industries and environmental protection agencies who can evaluate the variability of a specific parameter in time, what is very important piece of information for establishing corrective and preventive actions. This work presents a time series model of main physical, chemical and biological parameters of the Water Quality Index (WQI) determined for different selected points of a hydrographical basin form May/2006 to Aug/2010. The statistical model Arima enabled a better understanding of the physical, chemical and biological processes that most clearly influences WQI. The Arima model allowed the assessment of the trend of several parameters used in the calculation of the WQI, showing that dissolved oxygen, turbidity, total nitrogen, and fecal E. coli were highly correlated and are the parameters that caused the index changes over time.

A time series analysis of presentations to Queensland health facilities for alcohol-related conditions, following the increase in 'alcopops' tax

Objective: In response to concerns about the health consequences of high-risk drinking by young people, the Australian Government increased the tax on pre-mixed alcoholic beverages ('alcopops') favoured by this demographic. We measured changes in admissions for alcohol-related harm to health throughout Queensland, before and after the tax increase in April 2008. Methods: We used data from the Queensland Trauma Register, Hospitals Admitted Patients Data Collection, and the Emergency Department Information System to calculate alcohol-related admission rates per 100,000 people, for 15 - 29 year-olds. We analysed data over 3 years (April 2006 - April 2009), using interrupted time-series analyses. This covered 2 years before, and 1 year after, the tax increase. We investigated both mental and behavioural consequences (via F10 codes), and intentional/unintentional injuries (S and T codes). Results: We fitted an auto-regressive integrated moving average (ARIMA) model, to test for any changes following the increased tax. There was no decrease in alcohol-related admissions in 15 - 29 year-olds. We found similar results for males and females, as well as definitions of alcohol-related harms that were narrow (F10 codes only) and broad (F10, S and T codes). Conclusions: The increased tax on 'alcopops' was not associated with any reduction in hospital admissions for alcohol-related harms in Queensland 15 - 29 year-olds.

Real-time multipurpose reservoir operation: a case study / Exploitation en temps reacuteel d'un reservoir agrave buts multiples: eacutetude d'un cas

A real-time operational methodology has been developed for multipurpose reservoir operation for irrigation and hydropower generation with application to the Bhadra reservoir system in the state of Karnataka, India. The methodology consists of three phases of computer modelling. In the first phase, the optimal release policy for a given initial storage and inflow is determined using a stochastic dynamic programming (SDP) model. Streamflow forecasting using an adaptive AutoRegressive Integrated Moving Average (ARIMA) model constitutes the second phase. A real-time simulation model is developed in the third phase using the forecast inflows of phase 2 and the operating policy of phase 1. A comparison of the optimal monthly real-time operation with the historical operation demonstrates the relevance, applicability and the relative advantage of the proposed methodology.

The impact of antibiotic use on the incidence and resistance pattern of extended-spectrum beta-lactamase-producing bacteria in primary and secondary healthcare settings

Aims: The objective of the present study was to study the relationship between hospital antibiotic use, community antibiotic use and the incidence of extended-spectrum beta-lactamase (ESBL)-producing bacteria in hospitals, while assessing the impact of a fluoroquinolone restriction policy on ESBL-producing bacteria incidence rates. METHODS: The study was retrospective and ecological in design. A multivariate autoregressive integrated moving average (ARIMA) model was built to relate antibiotic use to ESB-producing bacteria incidence rates and resistance patterns over a 5 year period (January 2005-December 2009). Results: Analysis showed that the hospital incidence of ESBLs had a positive relationship with the use of fluoroquinolones in the hospital (coefficient = 0.174, P= 0.02), amoxicillin-clavulanic acid in the community (coefficient = 1.03, P= 0.03) and mean co-morbidity scores for hospitalized patients (coefficient = 2.15, P= 0.03) with various time lags. The fluoroquinolone restriction policy was implemented successfully with the mean use of fluoroquinolones (mainly ciprofloxacin) being reduced from 133 to 17 defined daily doses (DDDs)/1000 bed days (P <0.001) and from 0.65 to 0.54 DDDs/1000 inhabitants/day (P= 0.0007), in both the hospital and its surrounding community, respectively. This was associated with an improved ciprofloxacin susceptibility in both settings [ciprofloxacin susceptibility being improved from 16% to 28% in the community (P <0.001)] and with a statistically significant reduction in ESBL-producing bacteria incidence rates. Discussion: This study supports the value of restricting the use of certain antimicrobial classes to control ESBL, and demonstrates the feasibility of reversing resistance patterns post successful antibiotic restriction. The study also highlights the potential value of the time-series analysis in designing efficient antibiotic stewardship. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

Hospital antibiotic use and its relationship to age-adjusted comorbidity and alcohol-based hand rub consumption

SUMMARY The objective of this study was to evaluate the effect of age-adjusted comorbidity and alcohol-based hand rub on monthly hospital antibiotic usage, retrospectively. A multivariate autoregressive integrated moving average (ARIMA) model was built to relate the monthly use of all antibiotics grouped together with age-adjusted comorbidity and alcohol-based hand rub over a 5-year period (April 2005-March 2010). The results showed that monthly antibiotic use was positively related to the age-adjusted comorbidity index (concomitant effect, coefficient 1·103, P = 0·0002), and negatively related to the use of alcohol-based hand rub (2-month delay, coefficient -0·069, P = 0·0533). Alcohol-based hand rub is considered a modifiable factor and as such can be identified as a target for quality improvement programmes. Time-series analysis may provide a suitable methodology for identifying possible predictive variables that explain antibiotic use in healthcare settings. Future research should examine the relationship between infection control practices and antibiotic use, identify other infection control predictive factors for hospital antibiotic use, and evaluate the impact of enhancing different infection control practices on antibiotic use in a healthcare setting.

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.

Análise do investimento direto estrangeiro em Portugal utilizando a metodologia de box-jenkins

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientadora: Professora Doutora Patrícia Ramos

Análise do mecanismo de transmissão dos preços internacionais de commodities agrícolas sobre o comportamento da taxa de câmbio real no Brasil

This paper examined the transmission mechanism of international prices of agricultural commodities into the real exchange rate in Brazil for the period from January 2000 to February 2010. We used time series models (ARIMA Model, Transfer Model, Intervention Analysis, Johansen Cointegration Test) in determination of the short and long run elasticities. Transfer Function Model results show that changes in international prices of agricultural commodities are transmitted to the real exchange rate in Brazil in the short run, however, that transmission is less than unity, thus configuring the inelastic relationship. Johansen cointegration tests show that these variables are not co-integrated, no longer converge to the long-run equilibrium. These results are in agreement Cashim et al. (2004), which also found no long run relationship between real exchange rate and commodity prices in the case of Brazil. These results show that monetary shocks have greater weight on changes of the real exchange rate than real shocks.

Previsão da inflação no Boletim Focus: uma avaliação

Este trabalho investiga e analisa as diferenças das taxas anuais de inflação realizadas com relação às previsões dos agentes econômicos do mercado para um ano à frente. Os índices analisados foram o IPCA, IPA-M, IGP-M e o IGP-DI. Referente à previsão dos agentes para cada índice, foi feito uma análise estatística e uma análise de séries temporais através do modelo ARIMA. Este último explicou o erro de previsão dos agentes econômicos através de valores passados, ou defasados, do próprio erro de previsão, além dos termos estocásticos.

The dynamics of Mexican manufacturing exports

Includes bibliography

Banho de clorexidina para prevenção de colonização e infecção por micro-organismos multirresistentes na unidade de transplante de células tronco e hematopoiéticas

Introdução: Infecções relacionadas à assistência de saúde (IRAS) representam hoje um dos principais desafios da qualidade do cuidado do paciente, principalmente em pacientes submetido a transplante de células tronco e hematopoiéticas (TCTH) O banho diário com a clorexidina (CHG) degermante a 2% tem sido proposto principalmente em unidades de terapia intensivas (UTIs) para diminuir a colonização bacteriana do paciente e assim diminuir IRAS. O objetivo deste estudo foi avaliar o impacto do banho com CHG degermante a 2% em unidade de internação de TCTH na incidência de infecção e colonização por patógenos multirresistentes e ainda avaliar seu impacto na sensibilidade das bactérias ao antisséptico. Métodos: Foi realizado um estudo quasi-experimental, com duração de 9 anos, com início em janeiro/2005 até dezembro/2013. A intervenção foi iniciada em agosto de 2009, sendo que os períodos pré e pós-intervenção tiveram duração de 4,5 anos. As taxas de IRAS, infecção por gram-negativos multirresistentes e infecção e colonização por enterococo resistente a vancomicina (VRE) foram avaliadas através de série temporal, para estudar o impacto da intervenção. As concentrações inibitórias mínimas (CIM) das bactérias para a CHG com e sem o inibidor de bomba de efluxo (CCCP) foram avaliadas nos dois períodos. Os genes de resistência a CHG foram estudados por meio da PCR e a clonalidade dos isolados por eletroforese em campo pulsátil. Resultados: Foi observada redução significativa na incidência de infecção e colonização de VRE na unidade no período pós-intervenção (p: 0,001). Essa taxa permaneceu estável em outras UTIs clínicas do hospital. Contudo as taxas de infecção por Gram negativos multirresistentes aumentou nos últimos anos na unidade. Não ocorreu diminuição na taxa de IRAS na unidade. As CIMs testadas de CHG aumentaram nas amostras de VRE e K. pneumoniae após o período de exposição ao antisséptico, com queda importante da CIM após o uso do CCCP, revelando ser a bomba de efluxo, um importante mecanismo de resistência à CHG. As amostras de A. baumannii e P. aeruginosa não apresentaram aumento da CIM após período de exposição à clorexidina. As bombas de efluxo Ade A, B e C estiveram presentes na maioria dos A. baumannii do grupo controle (66%). A bomba cepA foi encontrada em 67% de todas as K. pneumoniae testadas e em 44,5% das P. aeruginosas do grupo pré intervenção. Observamos uma relação positiva entre a presença da CepA nas amostras de K. pneumoniae e a resposta ao CCCP: de todas as 49 amostras CepA positivas 67,3% obtiveram redução do seu MIC em 4 diluições após adição do CCCP. A avaliação de clonalidade demonstrou padrão policlonal das amostras de VRE, K. pneumoniae e A. baumannii avaliadas. Em relação às amostras de P. aeruginosa foi observado que no período pós-intervenção ocorreu predominância de um clone com > 80% semelhança em 10 das 22 amostras avaliadas pelo dendrograma. Conclusões: O banho de clorexidina teve impacto na redução da incidência de infecção e colonização por VRE na unidade de TCTH, e não teve o mesmo impacto nas bactérias gram-negativas. Os mecanismos moleculares de resistência à clorexidina estão intimamente ligados à presença de bomba de efluxo, sendo provavelmente o principal mecanismo de resistência e tolerância das bactérias ao antisséptico

Modeling Seasonal and Weather Impacts on Cycling Count

Thesis (Master's)--University of Washington, 2016-06