Relevant bibliographies by topics / Long time series / Dissertations / Theses
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Dissertations / Theses on the topic 'Long time series'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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1

Song, Li. "Piecewise models for long memory time series." Paris 11, 2010. http://www.theses.fr/2010PA112128.

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De nombreux travaux existent sur les processus stationnaires à longue mémoire (LM) et sur les modèles présentant des changements structurels. Cependant, il y a relativement peu de travaux sur les processus à LM non stationnaires faisant intervenir des ruptures, et ceci sans doute car LM et changement structurel sont deux phénomènes qu'il est facile de confondre. Dans cette thèse, nous considérons un modèle paramétrique de séries chronologiques à LM et non stationnaires : le processus localement autorégressif à moyenne mobile fractionnairement intégrée (FARlMA). Dans ce modèle, le nombre et les
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2

Thyer, Mark Andrew. "Modelling long-term persistence in hydrological time series." Diss., 2000, 2000. http://www.newcastle.edu.au/services/library/adt/public/adt-NNCU20020531.035349/index.html.

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3

Arteche, Jesus Maria. "Seasonal and cyclical long-memory in time series." Thesis, London School of Economics and Political Science (University of London), 1998. http://etheses.lse.ac.uk/2077/.

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This thesis deals with the issue of persistence, focusing on economic time series, and extending the subject to seasonal and cyclical long memory time series. Such processes are defined. In the frequency domain they are characterized by spectral poles/zeros at some frequency ω between 0 and π. First we review some of the work done to date on seasonality and long memory, and we focus on research that try to link both issues. One of the limitations of the existing work is the imposition of asymptotic symmetry in the spectral density around ω. We describe some processes that allow for spectral as
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4

Fraser, William Stuart Alistair. "An analysis of long memory vector time series." Thesis, University of Warwick, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389715.

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5

Algarhi, Amr Saber Ibrahim. "Essays on long memory time series and fractional cointegration." Thesis, University of Exeter, 2013. http://hdl.handle.net/10871/13791.

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The dissertation considers an indirect approach for the estimation of the cointegrating parameters, in the sense that the estimators are jointly constructed along with estimating other nuisance parameters. This approach was proposed by Robinson (2008) where a bivariate local Whittle estimator was developed to jointly estimate a cointegrating parameter along with the memory parameters and the phase parameters (discussed in chapter 2). The main contributions of this dissertation is to establish, similar to Robinson (2008), a joint estimation of the memory, cointegrating and phase parameters in s
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6

Lazarova, Stepana. "Long memory and structural breaks in time series models." Thesis, London School of Economics and Political Science (University of London), 2006. http://etheses.lse.ac.uk/1927/.

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This thesis examines structural breaks in time series regressions where both regressors and errors may exhibit long range dependence. Statistical properties of methods for detecting and estimating structural breaks are analysed and asymptotic distribution of estimators and test statistics are obtained. Valid bootstrap methods of approximating the limiting distribution of the relevant statistics are also developed to improve on the asymptotic approximation in finite samples or to deal with the problem of unknown asymptotic distribution. The performance of the asymptotic and bootstrap methods ar
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7

Leschinski, Christian Hendrik [Verfasser]. "Essays on long memory time series / Christian Hendrik Leschinski." Hannover : Technische Informationsbibliothek (TIB), 2016. http://d-nb.info/1112948805/34.

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8

Jaunzems, Davis. "Time-series long-term forcasting for A/B tests." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205344.

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Den tekniska utvecklingen av datorenheter och kommunikationsverktyg har skapat möjligheter att lagra och bearbeta större mängder information än någonsin tidigare. För forskare är det ett sätt att göra mer exakta vetenskapliga upptäckter, för företag är det ett verktyg för att bättre förstå sina kunder, sina produkter och att skapa fördelar gentemot sina konkurrenter. Inom industrin har A/B-testning blivit ett viktigt och vedertaget sätt att skaffa kunskaper som bidrar till att kunna fatta datadrivna beslut. A/B-test är en jämförelse av två eller flera versioner för att avgöra vilken som funger
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9

Andersson, Michael K. "On testing and forecasting in fractionally integrated time series models." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics [Ekonomiska forskningsinstitutet vid Handelshögsk.] (EFI), 1998. http://www.hhs.se/efi/summary/467.htm.

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10

Ellis, Craig, of Western Sydney Macarthur University, and Faculty of Business and Technology. "An investigation of long-term dependence in time-series data." THESIS_FBT_XXX_Ellis_C.xml, 1998. http://handle.uws.edu.au:8081/1959.7/242.

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Traditional models of financial asset yields are based on a number of simplifying assumptions. Among these are the primary assumptions that changes in asset yields are independent, and that the distribution of these yields is approximately normal. The development of financial asset pricing models has also incorporated these assumptions. A general feature of the pricing models is that the relationship between the model variables is fundamentally linear. Recent empirical research has however identified the possibility for these relations to be non-linear. The empirical research focused primarily
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11

Bružaitė, Kristina. "Some linear models of time series with nonstationary long memory." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090312_091000-74094.

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In the thesis is studied the limit distribution of partial sums of certain linear time series models with nonstationary long memory and certain statistics which involve partial sums processes. Philippe, Surgailis, Viano (2006, 2008) introduced time-varying fractionally integrated filters and studied the limit distribution of partial sums processes of these filters under finite variance set-up. In the thesis is studied the limit distribution of partial sums processes of infinite variance time-varying fractionally integrated filters. We assume that the innovations belong to the domain of attract
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12

Modlin, Danny Robert. "Utilizing time series analysis to forecast long-term electrical consumption /." Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/modlind/dannymodlin.pdf.

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13

Ellis, Craig. "An investigation of long-term dependence in time-series data /." View thesis, 1998. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030723.150913/index.html.

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14

Henry, Marc. "Long memory in time series : semiparametric estimation and conditional heteroscedasticity." Thesis, London School of Economics and Political Science (University of London), 1999. http://etheses.lse.ac.uk/1581/.

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This dissertation considers semiparametric spectral estimates of temporal dependence in time series. Semiparametric frequency domain methods rely on a local parametric specification of the spectral density in a neighbourhood of the frequency of interest. Therefore, such methods can be applied to the analysis of singularities in the spectral density at frequency zero to identify long memory. They can also serve as the basis for the estimation of regular parts of the spectrum. One thereby avoids inconsistency that might arise from misspecification of dynamics at frequencies other than the freque
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15

Holt, Karen Sofie Sollie. "Statistical Modelling and Inference for Long Gene Expression Time Series." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-24626.

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The main objective of this thesis is to model and analyse long gene expression time series from a microarray study using the linear mixed effects model. This regression model is widely used in the fields of biology, ecology and medicine. The linear mixed effects model combines both fixed and random effects on a linear scale. We will use data from a microarray study conducted by Astrid Lægreid & Torunn Bruland and collaborators at Department of Cancer Research and Molecular Medicine (IKM) at Norwegian University of Science and Technology (NTNU) in 2009. The data set consists of paired
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16

Busch, Marie Theres [Verfasser]. "Essays on spurious long memory time series / Marie Theres Busch." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2018. http://d-nb.info/1162620765/34.

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17

da, Silva Afonso Goncalves. "Fractional cointegration analysis of nonlinear time series with long memory." Thesis, London School of Economics and Political Science (University of London), 2008. http://etheses.lse.ac.uk/2166/.

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This thesis develops theoretical tools for fractional cointegration analysis of nonlinear time series. These tools are employed to establish consistency of narrow band versions of Least Squares and Principal Components, in situations when the observables do not follow traditional linear process assumptions. Chapter 1 introduces the problem, and Chapter 2 reviews the tools and techniques used in the literature for analysing stationary fractional cointegration, emphasizing methods that will be the focus of subsequent chapters. Chapter 3 considers a bivariate factor model, where the unobservable
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18

Zhou, Yinghui. "Estimating the fractional differencing parameter, d, of a long memory time series and simulating stationary and invertible time series." Thesis, University of East Anglia, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323223.

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19

Ma, Sai-shing, and 馬世晟. "On the long memory autoregressive conditional duration models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/197101.

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In financial markets, transaction durations refer to the duration time between two consecutive trades. It is common that more frequent trades are expected to be followed by shorter durations between consecutive transactions, while less frequent trades are expected to be followed by longer durations. Autoregressive conditional duration (ACD) model was developed to model transaction durations, based on the assumption that the expected average duration is dependent on the past durations. Empirically, transaction durations possess much longer memory than expected. The autocorrelation functions
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20

Bilayi-Biakana, Clémonell Lord Baronat. "Regularly Varying Time Series with Long Memory: Probabilistic Properties and Estimation." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40083.

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We consider tail empirical processes for long memory stochastic volatility models with heavy tails and leverage. We show a dichotomous behaviour for the tail empirical process with fixed levels, according to the interplay between the long memory parameter and the tail index; leverage does not play a role. On the other hand, the tail empirical process with random levels is not affected by either long memory or leverage. The tail empirical process with random levels is used to construct a family of estimators of the tail index, including the famous Hill estimator and harmonic moment estimators.
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21

Belkhouja, Mustapha. "Modelling nonlinearities in long-memory time series : simulation and empirical studies." Thesis, Aix-Marseille 2, 2010. http://www.theses.fr/2010AIX24010/document.

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Cette thèse porte sur l'identification et l'estimation des ruptures structurelles pouvant affecter des données économiques et financières à mémoire longue. Notre étude s'est limitée dans les trois premiers chapitres au cadre univarié où nous avons modélisé la dépendance de long terme et les changements structurels simultanément et séparément au niveau de la moyenne ainsi que la volatilité. Dans un premier temps nous n'avons tenu compte que des sauts instantanés d'état ensuite nous nous sommes intéressés à la possibilité d'avoir des changements graduels et lisses au cours du temps grâce à des m
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22

Li, Muyi, and 李木易. "Statistical inference on some long memory volatility models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46482970.

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23

Andrianova, Anna. "Simulation of temperature time-series on long time scales with application to pricing weather derivatives." Thesis, London School of Economics and Political Science (University of London), 2009. http://etheses.lse.ac.uk/3003/.

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Long term weather forecasts are in great demand across many industries, such as the agricultural, tourism, and energy sectors. In this thesis a new long-term temperature forecasting benchmark is proposed. In particular, the Ensemble Random Analog Prediction (ERAP) dynamic resampler is developed. ERAP allows one to generate temperature scenarios over long time scales without making assumptions about the underlying model of temperature. ERAP works by identifying similar patterns in the historical data across multiple time scales. We also propose a new non-linear weather resembling test system -
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24

Bonato, Tommaso. "Time Series Predictions With Recurrent Neural Networks." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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L'obiettivo principale di questa tesi è studiare come gli algoritmi di apprendimento automatico (machine learning in inglese) e in particolare le reti neurali LSTM (Long Short Term Memory) possano essere utilizzati per prevedere i valori futuri di una serie storica regolare come, per esempio, le funzioni seno e coseno. Una serie storica è definita come una sequenza di osservazioni s_t ordinate nel tempo. Inoltre cercheremo di applicare gli stessi principi per prevedere i valori di una serie storica prodotta utilizzando i dati di vendita di un prodotto cosmetico durante un periodo di tre anni.
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25

Craigmile, Peter Francis. "Wavelet-based estimation for trend contaminated long memory processes /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/8967.

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26

Rea, William Stanley. "The Application of Atheoretical Regression Trees to Problems in Time Series Analysis." Thesis, University of Canterbury. Mathematics and Statistics, 2008. http://hdl.handle.net/10092/1715.

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This thesis applies Atheoretical Regression Trees (ART) to the problem of locating changes in mean in a time series where the number and location of those changes are unknown. We undertook an extensive simulation study into ART's performance on a range of time series. We found ART to be a useful addition to currently established structural break methodologies such as the CUSUM and that due to Bai and Perron. ART was found to be useful in the analysis of long time series which are not practical to analyze with the optimal procedure of Bai and Perron. ART was applied to a long standing problem
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27

Quoreshi, Shahiduzzaman. "Time series modelling of high frequency stock transaction data." Doctoral thesis, Umeå : Department of Economics, Umeå universitet, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-757.

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28

Edwards, Samuel Zachary. "Forecasting Highly-Aggregate Internet Time Series Using Wavelet Techniques." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/33223.

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The U.S. Coast Guard maintains a network structure to connect its nation-wide assets. This paper analyzes and models four highly aggregate traces of the traffic to/from the Coast Guard Data Network ship-shore nodes, so that the models may be used to predict future system demand. These internet traces (polled at 5â 40â intervals) are shown to adhere to a Gaussian distribution upon detrending, which imposes limits to the exponential distribution of higher time-resolution traces. Wavelet estimation of the Hurst-parameter is shown to outperform estimation by another common method (Sample-Var
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29

Santos, Bruno Reis dos. "Influencia local em modelos de series temporais." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306151.

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Orientador: Mauricio Enrique Zevallos Herencia<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Ciencia da Computação<br>Made available in DSpace on 2018-08-11T01:10:13Z (GMT). No. of bitstreams: 1 Santos_BrunoReisdos_M.pdf: 1935776 bytes, checksum: f3579f38b051dcbc18a4a0f79c2d6ab2 (MD5) Previous issue date: 2008<br>Resumo: Nesta dissertação é discutido o uso da metodologia de diagnóstico de Influência Local em modelos de séries temporais. Especificamente, serão estudados os modelos autoregressivos de ordem um, os modelos de regressão com
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30

Stone, Léonie L. "Intra-industry trade in the long run : a multi-country, time-series study /." Connect to resource, 1992. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1262290072.

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31

Stone, Leonie Lindsley. "Intra-industry trade in the long run : a multi-country, time-series study." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1262290072.

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32

Stone, Léonie L. "Intra-industry trade in the long run : a multi-country, time-series study /." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487777170405466.

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33

Konda, Sreenivas. "FITTING MODELS OF NONSTATIONARY TIME SERIES: AN APPLICATION TO EEG DATA." online version, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1149265141.

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34

Khalfaoui, Rabeh. "Wavelet analysis of financial time series." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM1083.

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Cette thèse traite la contribution des méthodes d'ondelettes sur la modélisation des séries temporelles économiques et financières et se compose de deux parties: une partie univariée et une partie multivariée. Dans la première partie (chapitres 2 et 3), nous adoptons le cas univarié. Premièrement, nous examinons la classe des processus longue mémoire non-stationnaires. Une étude de simulation a été effectuée afin de comparer la performance de certaines méthodes d'estimation semi-paramétrique du paramètre d'intégration fractionnaire. Nous examinons aussi la mémoire longue dans la volatilité en
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35

SOUZA, LEONARDO ROCHA. "THE INFLUENCE OF THE SAMPLING INTERVAL IN THE LONG MEMORY ESTIMATION IN TIME SERIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2001. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=1428@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Esta tese de doutorado relaciona a estimação da diferenciação fracionária, como medida de memória longa, com o intervalo de tempo entre observações contíguas de uma série temporal. Em teoria, o grau de diferenciação é constante em relação à diminuição da freqüência de observação, não importando se para diminuir a freqüência de observação ignore-se as observações intermediárias ou agregue-se as observações temporalmente. Entretanto, para o caso de se obter séries amostradas a uma freqüência mais baixa através de se ignorar ob
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36

Aparicio, Acosta Felipe Miguel. "Nonlinear modelling and analysis under long-range dependence with an application to positive time series /." [S.l.] : [s.n.], 1995. http://library.epfl.ch/theses/?nr=1381.

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37

Zhou, Zhiwei. "The applications of InSAR time series analysis for monitoring long-term surface change in peatlands." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4875/.

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In the past three decades, peatlands all over the world such as upland bogs, tropical fens, have been undergoing significant and rapid degradations. These degradations cause carbon loss and CO2 emissions, and also fuel climate change. In this research, I present three case studies on how space geodetic tools, especially Radar Interferometry (InSAR), can be used to monitor and to advance our understanding of the long-term surface changes in peatlands. First, I investigate the eroding extent and severity of upland UK peatlands using InSAR. Both short wavelength C-band and long wavelength L-band
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38

Li, Yuntao. "Federated Learning for Time Series Forecasting Using Hybrid Model." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254677.

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Time Series data has become ubiquitous thanks to affordable edge devices and sensors. Much of this data is valuable for decision making. In order to use these data for the forecasting task, the conventional centralized approach has shown deficiencies regarding large data communication and data privacy issues. Furthermore, Neural Network models cannot make use of the extra information from the time series, thus they usually fail to provide time series specific results. Both issues expose a challenge to large-scale Time Series Forecasting with Neural Network models. All these limitations lead to
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39

Rahmani, Mohammadsaeid. "Volatility Modelling Using Long-Memory- GARCH Models, Applications of S&P/TSX Composite Index." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35064.

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The statements that include sufficient detail to identify the probability distributions of future prices are asset price dynamics. In this research, using the empirical methods that could explain the historical prices and discuss about how prices change we investigate various important characteristics of the dynamics of asset pricing. The volatility changes can explain very important facts about the asset returns. Volatility could gauge the variability of prices over time. In order to do the volatility modelling we use the conditional heteroskedasticitc models. One of the most powerful tools t
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40

Dienst, Manuel [Verfasser]. "Detection, documentation and homogenization of urban heat island effects in long temperature time series / Manuel Dienst." Mainz : Universitätsbibliothek Mainz, 2018. http://d-nb.info/1171741693/34.

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41

Butcher, John B. "Reservoir Computing with high non-linear separation and long-term memory for time-series data analysis." Thesis, Keele University, 2012. http://eprints.keele.ac.uk/1185/.

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Left unchecked the degradation of reinforced concrete can result in the weakening of a structure and lead to both hazardous and costly problems throughout the built environment. In some cases failure to recognise the problem and apply appropriate remedies has already resulted in fatalities. The problem increases with the age of any structures and consequently has become more pressing throughout the latter half of the 20th century. It is therefore of paramount importance to assess and repair these structures using an accurate and cost-effective approach. ElectroMagnetic Anomaly Detection (EMAD)
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Costa, Maria da Conceição Cristo Santos Lopes. "Optimal alarms systems and its application to financial time series." Doctoral thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/12872.

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Doutoramento em Matemática<br>This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking i
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Sato, Joao Ricardo. "Processos com memória longa compartilhada." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-22082007-160332/.

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Este trabalho tem como objetivo a avaliação de três estimadores do parâmetro de integração fracionária d e de um teste para memória longa compartilhada. Os estimadores a serem avaliados são: o estimador de Geweke e Porter-Hudak, o estimador usando o periodograma suavizado e o estimador semiparamétrico truncado de Whittle. A avaliação dos estimadores será no contexto de processos ARFIMA+ARMA, e em relação a variações nos termos autoregressivos e de médias móveis, tanto do termo de memória curta quanto do termo de memória longa. Além disso, serão introduzidos o conceito de modelos com memória lo
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44

Norouzi, Mehdi. "Tracking Long-Term Changes in Bridges using Multivariate Correlational Data Analysis." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1416570591.

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45

Díaz, González Fernando. "Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254665.

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Federated learning poses a statistical challenge when training on highly heterogeneous sequence data. For example, time-series telecom data collected over long intervals regularly shows mixed fluctuations and patterns. These distinct distributions are an inconvenience when a node not only plans to contribute to the creation of the global model but also plans to apply it on its local dataset. In this scenario, adopting a one-fits-all approach might be inadequate, even when using state-of-the-art machine learning techniques for time series forecasting, such as Long Short-Term Memory (LSTM) netwo
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46

Zeng, Ning. "The usefulness of econometric models with stochastic volatility and long memory : applications for macroeconomic and financial time series." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3903.

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This study aims to examine the usefulness of econometric models with stochastic volatility and long memory in the application of macroeconomic and financial time series. An ARFIMA-FIAPARCH process is used to estimate the two main parameters driving the degree of persistence in the US real interest rate and its uncertainty. It provides evidence that the US real interest rates exhibit dual long memory and suggests that much more attention needs to be paid to the degree of persistence and its consequences for the economic theories which are still inconsistent with the finding of either near-unit-
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47

Lindell, Adam. "Pulse Repetition Interval Time Series Modeling for Radar Waves using Long Short-Term Memory Artificial Recurrent Neural Networks." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-377865.

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This project is a performance study of Long Short-Term Memory artificial neural networks in the context of a specific time series prediction problem consisting of radar pulse trains. The network is tested both in terms of accuracy on a regular time series but also on an incomplete time series where values have been removed in order to test its robustness/resistance to small errors. The results indicate that the network can perform very well when no values are removed and can be trained relatively quickly using the parameters set in this project, although the robustness of the network seems to
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48

Borges, Cristiano Amâncio Vieira. "Modelos lineares generalizadas para series temporais com memoria longa." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306149.

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Orientador: Mauricio Enrique Zevallos Herencia<br>Dissertação (mestrado) - Universidade Estadadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica<br>Made available in DSpace on 2018-08-15T13:14:28Z (GMT). No. of bitstreams: 1 Borges_CristianoAmancioVieira_M.pdf: 2172730 bytes, checksum: 3a0a212a114d920caf7bafe3f7a04868 (MD5) Previous issue date: 2010<br>Resumo: A modelagem de séries temporais não gaussianas é um tema de alta relevância na análise de séries temporais. Utilizando-se de estimação por verossimilhança parcial, Kedem e Fokianos (2002) estenderam sistemat
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49

Snguanyat, Ongorn. "Stochastic modelling of financial time series with memory and multifractal scaling." Queensland University of Technology, 2009. http://eprints.qut.edu.au/30240/.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of
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50

Betken, Annika [Verfasser], Herold [Gutachter] Dehling, and Holger [Gutachter] Dette. "Change-point analysis for long-range dependent time series / Annika Betken ; Gutachter: Herold Dehling, Holger Dette ; Fakultät für Mathematik." Bochum : Ruhr-Universität Bochum, 2018. http://d-nb.info/116194205X/34.

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