Recently, computational methods and software have been receiving more attention in the econometrics literature, emphasizing that they are integral components of modern econometric research. This has also promoted the development of many new econometrics software packages written in R and made available on the Comprehensive R Archive Network. This special volume on "Econometrics in R" features a selection of these recent activities that includes packages for econometric analysis of cross-section, time series and panel data. This introduction to the special volume highlights the contents of the contributions and embeds them into a brief overview of other past, present, and future projects for econometrics in R.

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Electrical stimulation applied to the common peroneal nerve during the swing phase of gait is an established clinical technique for the correction of dropped foot following upper motor neuron injury. The catch-like effect of skeletal muscle refers to force augmentation resulting from the inclusion of an initial high frequency burst of two or more stimuli prior to conventional low frequency electrical stimulation. There is interest in clinical utilisation of catch-like stimulation during functional applications; however the mechanism of the effect is not fully understood. The purpose of this research was to determine if the catch-like effect is a property of the muscle alone or related to spinal reflex mediated activation. In order to investigate this, direct and reflex motor effects of conventional and catch-like stimulation during dropped foot correction and other controlled conditions were assessed in unimpaired (n=12) and stroke (n=13) populations through use of electromyography. A system was developed to enable analysis of electromyography activity shortly after the application of configurable stimulation patterns. Innovative design minimised effects of stimulation artefact such that electromyography of the tibialis anterior and soleus muscles during dropped foot correction could be assessed. This system was utilised and further refined during exploratory investigations prior to structured use with study participants. Both direct and reflex motor effects of conventional stimulation were found to vary with muscle length. At typical stimulation intensities and frequencies used during dropped foot correction, direct (orthodromic) motor activation dominates voluntary or reflex mediated activation of the tibialis anterior. Enhanced contractile force when utilising catch-like stimulation with human participants, appears an effect solely inherent to muscle with no excitatory or inhibitory spinal reflex contribution. Facilitation of reflected antidromic motor activation (F-waves) with voluntary effort, observed only within the unimpaired participant group, may be an indicator of normal neuroplasticity at the spinal cord. Findings highlight the need to consider antidromic motor effects of electrical stimulation when combining its use with voluntary function during future clinical development.

ICT enabled body-worn remote rehabilitation system has been projected as an effective means for combating the major socio-economic challenge resulting from the need for quality care delivery for stroke survivors. The two major problems faced in such systems are: 1) while effective for characterising the patient’s performance during a constrained “exercise phase” in remote settings, the more natural indicator of rehabilitation status, i.e., the patient’s performance in an “unconstrained nomadic environment”, are often not considered and; 2) being body-worn and thus constrained by the battery life, their sustainability for long-term continuous monitoring is questionable. These shortcomings motivated the: 1) exploration of effective algorithmic strategies for accurately detecting movement of affected body parts, more specifically, the movement of the upper limb since it frequently gets affected by stroke episodes – in unconstrained scenarios and; 2) translation of the algorithms to dedicated low-power hardware with an aim of enhancing the battery life of a resource constrained body-worn sensor based remote rehabilitation system for its sustained operation satisfying the notion of long-term continuous monitoring. Following instructions of expert physiotherapists, this work concentrates on detecting three fundamental upper limb movements in unconstrained scenarios: extension/flexion of the forearm; rotation of the forearm about the elbow; and rotation of the arm about the long axis of forearm, using body-worn inertial sensors. After selecting the appropriate type of inertial sensors and their positions through exhaustive experiments, two novel algorithms were proposed to recognize the above mentioned movements: 1) clustering and minimum distance classifier based approach and 2) tracking the orientation of an inertial sensor placed on the wrist. The performances of the algorithms have been evaluated prospectively through an archetypal activity ‘making-a-cup-of-tea’ which includes multiple occurrences of the chosen movements. The proposed clustering based approach detected the three movements with an average accuracy of 88% and 70% using accelerometer data and 83% and 70% using gyroscope data obtained from the wrist for healthy subjects and stroke survivors respectively. Compared to that the proposed sensor orientation based methodology using a wrist-worn accelerometer only recognized the three movements with accuracies in the range of 91-99% for healthy subjects and 70%-85% for stroke survivors. However the clustering based approach provides greater flexibility in terms of incorporating new types of movements apart from the ones chosen here and can also be used to track changes in motor functionality over time. Subsequently it was translated into a novel ASIC resulting in dynamic power consumption of 25.9 mW @20 MHz in 130 nm technology. On the other hand, the sensor orientation based approach was also validated in hardware using an Altera DEII FPGA system, for high speed real-time movement recognition.

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Non-adherence to clinical guidelines has been identified as a consistent finding in general practice. The purpose of this research was to develop and evaluate theory-informed, computer-delivered interventions to promote the implementation of guidelines in general practice, which GPs viewed as feasible and acceptable. The intervention aimed to promote guideline adherence for antibiotic prescribing in respiratory tract infections, and adherence to recommendations for secondary stroke prevention. An intervention development study involved the creation of computer-delivered prompts using aspects of social cognitive theory, and drawing on nationally recommended standards for clinical content. Prompts were presented to GPs during interviews, and iteratively refined based on feedback. GPs reported being more likely to use prompts if they were perceived as offering support and choice, as opposed to being an enforcement method. The prompts were then entered into a trial (not reported) and two process evaluation studies were conducted with GPs who had taken part in the trial. A qualitative evaluation study involving interviews with GPs, revealed that the prompts were perceived as useful and acceptable in practice, but GPs who had not been informed of the prompts appearance reported being less likely to engage with them. A quantitative evaluation study involved a questionnaire consisting of theory based measures and an intervention evaluation measure. GPs were satisfied with the usability of the prompts, and intervention group GPs reported higher levels of self-efficacy in managing patients according to guidelines compared to control group GPs. Overall the intervention was viewed as feasible and acceptable. A key characteristic of an acceptable computer-delivered intervention appears to be that it should be perceived as a useful tool supporting GP practice. However, conclusions of the evaluation were limited by a small and potentially non-representative sample of trial GPs.

Analysis of several acceptance sampling procedures is performed and improvement of the procedures is sug- gested in this thesis. The issue of an efficient calculation of exact (P1, P2) single sampling plans for sampling by variables and exact LTPD and AOQL single sampling plans for sampling by variables when the rejected lots are inspected is addressed. The calculation of the plans is done using exact formula for operating characteristic of acceptance sampling plan and the new plans have better characteristics compared to the plans computed in a usual way using just approximately valid formula for operating characteristic. The tables of plans calculated according to procedures suggested in this thesis are provided for a couple of input parameters combinations. Tools designed for working with acceptance sampling plans, tools for analysis and calculation of acceptance sampling plans is one of the outputs of this thesis. R language and environment for statistical computations was chosen for implementation. The tools are satisfactorily efficient and may be easily used even for acceptance sampling plans tables computation. Newly defined functions in R are supplied including their source code and basic documentation so that acceptance sampling plans can be computed as demanded in case that the particular input parameters set is out of the scope covered in the tables of plans provided here.

Submitted by admin tede (tede@pucgoias.edu.br) on 2017-08-10T18:29:13Z No. of bitstreams: 1 REGINA DUARTE RIBEIRO MELO.pdf: 4787890 bytes, checksum: f1e4799a54a2be2090102e3ea15abdda (MD5) / Made available in DSpace on 2017-08-10T18:29:13Z (GMT). No. of bitstreams: 1 REGINA DUARTE RIBEIRO MELO.pdf: 4787890 bytes, checksum: f1e4799a54a2be2090102e3ea15abdda (MD5) Previous issue date: 2017-04-06 / This paper presents the application of Complex Networks Theory and Analysis of Social Networks (ARS) to evaluate the scientific production of the Academic Postgraduate Programs in Production Engineering. The data were collected in the Sucupira Platform (PS) for the period from 2013 to 2015, part of the current evaluation quadrennium (2013 to 2016). The database was arranged in Excel spreadsheets with the variables acquired from the PS. The data were transformed from the extension xlsx to csv, when compatibilizing them for use of software R, version 3.1.1 and environment RStudio 0.99.891. The developed scripts used the Igraph, Network, Bipartite and Ggraph packages that were suitable for bipartite network analysis. The study of the demographic patterns of collaboration between programs indicates that these are stronger among programs from the same region. The production patterns of the CAPES 3 programs indicated the production of the 1437 articles in the period, most of which are from strata B5 and lower production in upper strata (A1, A2 and B1), in which 5002 employees participated, Of external participants. When analyzing the standards of all the programs, it was noticed that the CAPES concepts of the programs obtained in the triennium 2010-2012 did not imply in the higher productions in the upper strata. The most wanted journals for publications in A1 (Journal of Cleaner Production, with 18.51%), for A2 (Energy Policy with 8.11%) and B1 (International Journal, Advanced Manufacturing Technology with 6.44%). The ARS corroborated in the exploration of the data in bipartite network evidencing its potential of analysis and visualization. / Este trabalho apresenta a aplicação da Teoria de Redes Complexas e Análise de Redes Sociais (ARS) para avaliação da produção científica dos Programas de Pós-graduação Acadêmicos em Engenharia de Produção. Os dados foram coletados na Plataforma Sucupira (PS) para o período de 2013 a 2015, parte do quadriênio de avaliação atual (2013 a 2016). A base de dados foi disposta em planilhas do Excel com as variáveis adquiridas da PS. Os dados foram transformados da extensão xlsx para csv, ao compatibilizá-los para utilização do software R, versão 3.1.1 e ambiente RStudio 0.99.891. Os scripts desenvolvidos utilizaram os pacotes Igraph, Network, Bipartite e Ggraph que foram adequados para as análises das redes bipartidas. O estudo dos padrões demográficos de colaboração entre os programas aponta que estes são mais fortes entre programas de mesma região. Os padrões de produção dos programas conceito CAPES 3 indicaram a produção dos 1437 artigos no período, em que a maioria são do estrato B5 e menor produção em estratos superiores (A1, A2 e B1), nos quais participaram 5002 colaboradores, que são em maioria de participantes externos. Quando analisados os padrões de todos os programas notou-se que os conceitos CAPES dos programas obtidos no triênio 2010-2012 não implicaram nas maiores produções nos estratos superiores. Os periódicos mais procurados para publicações em A1 (Journal of Cleaner Production, com 18,51%), para A2 (Energy Policy, com 8,11%) e B1 (International Journal, Advanced Manufacturing Technology, com 6,44%). A ARS corroborou na exploração dos dados em rede bipartida evidenciando seu potencial de análise e visualização.

Open source software (OSS) is typically created in a decentralized self-organizing process by a community of developers having the same or similar interests. A key factor for the success of OSS over the last two decades is the internet: Developers who rarely meet face-to-face can employ new means of communication, both for rapidly writing and deploying software. Therefore, many tools emerged that assist a collaborative software development process, including in particular tools for source code management (SCM) and version control. In the R world, SCM is not a new idea, in fact, the R Development Core Team has always been using SCM tools for the R sources; first by means of Concurrent Versions System (CVS), and then via Subversion (SVN). A central repository is hosted by ETH Zürich mainly for managing the development of the base R system. Mailing lists like R-help, R-devel and many others are currently the main communication channels in the R community. Also beyond the base system, many R contributors employ SCM tools for managing their R packages, e.g., via web-based SVN repositories like SourceForge (http://SourceForge.net/) or Google Code (http://Code.Google.com/). However, there has been no central SCM repository providing services suited to the specific needs of R package developers. Since early 2007, the R-project offers such a central platform to the R community. R-Forge (http://R-Forge.R-project.org/) provides a set of tools for source code management and various web-based features. It aims to provide a platform for collaborative development of R packages, R-related software or further projects. / Series: Research Report Series / Department of Statistics and Mathematics

Personalised medicine for cancer treatment promises benefits for patient survival and effective use of medical resources. This goal requires the development of predictive models for the identification and implementation of biomarkers for the prediction of patient survival given treatment options. This thesis addresses research questions in this area. The systematic review detailed in Chapter 2 investigates the literature concerning the prediction of resistance to chemotherapy for ovarian cancer patients using statistical methods and gene expression measurements. The range of models used by studies in the systematic review highlights the popularity of traditional models, such as Cox proportional hazards, with few more complex models being utilised. In Chapters 3 and 4, new methods are presented for modelling right-censored survival data. Due to the nature of biomedical data, the methods used need to be flexible and adequately account for high dimensional, noisy data. Gaussian processes fulfil these requirements and were hence used for the development of three Gaussian process models for right-censored survival data. Chapter 3 details these models, and they are applied to synthetic and cancer data in Chapter 4. In all cases the Gaussian processes for survival were found to equal or outperform all comparison models, as measured by concordance index. Given the application to molecular cancer data, it was expected that the data would be high dimensional. Two feature selection methods are investigated in Chapter 5 for use with Gaussian processes to address this. In Chapter 6 a program is developed for the analysis of the data produced by a test for cancer mutations using qPCR. The automated program was designed to isolate the analysis from the user and produce results and reports for clinical use. It is observed that this approach of automated analysis would be suitable for application to any form of clinical test or complex predictive model without the requirement of user guidance.