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Tesi sul tema "Mathematics Outlines"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 8 febbraio 2022

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1

Breetzke, Peter Roland. "Sequence in the mathematics syllabus : an investigation of the Senior Secondary Mathematics Syllabus (July 1984) of the Cape Education Department attempting to reconcile the demands of the strictly mathematical order and the developmental needs of pupils, modified by the mathematical potential of the electronic calculator : some teaching strategies resulting from new influences in the syllabus." Thesis, Rhodes University, 1988. http://hdl.handle.net/10962/d1001430.

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This study was motivated by the latest revision of the mathematics syllabuses of the Cape Education Department. The most important changes to content in the Senior Secondary Mathematics Syllabus (July 1984) are the introduction of calculus and linear programming, the substitution of a section on analytical geometry for vector algebra and the recall of the remainder and factor theorems. The way in which these changes were introduced left the task of integrating them into the teaching process in the hands of individual teachers. This is a task of extreme importance. If one's classroom practice i

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2

Robson, Geoffrey. "Multiple outlier detection and cluster analysis of multivariate normal data." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53508.

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Thesis (MscEng)--Stellenbosch University, 2003.<br>ENGLISH ABSTRACT: Outliers may be defined as observations that are sufficiently aberrant to arouse the suspicion of the analyst as to their origin. They could be the result of human error, in which case they should be corrected, but they may also be an interesting exception, and this would deserve further investigation. Identification of outliers typically consists of an informal inspection of a plot of the data, but this is unreliable for dimensions greater than two. A formal procedure for detecting outliers allows for consistency when

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3

Dunagan, John D. (John David) 1976. "A geometric theory of outliers and perturbation." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8396.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2002.<br>Includes bibliographical references (p. 91-94).<br>We develop a new understanding of outliers and the behavior of linear programs under perturbation. Outliers are ubiquitous in scientific theory and practice. We analyze a simple algorithm for removal of outliers from a high-dimensional data set and show the algorithm to be asymptotically good. We extend this result to distributions that we can access only by sampling, and also to the optimization version of the problem. Our results cover both the discrete an

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4

Kuo, Jonny. "Outlier detection for overnight index swaps." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-173378.

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I examensarbetet undersöks metoder för anomalidetektion i tidsserie data. Givet data för overnight index swaps (SEK), så har syntetiskt data skapats med olika ty-per av anomalier. Jämförelse mellan algoritmerna Isolation forest och Local outlierfactor görs genom att mäta respektive prestande för de syntetiska dataseten mot Accuracy, Precision, Recall, F-measure och Matthews correlation coefficient.<br>In the thesis, methods for anomaly detection in time series data are investigated. Given data for overnight index swaps (SEK), synthetic data has been created with different types of anomalies. C

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5

Schall, Robert. "Outliers and influence under arbitrary variance." Doctoral thesis, University of Cape Town, 1986. http://hdl.handle.net/11427/21913.

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Using a geometric approach to best linear unbiased estimation in the general linear model, the additional sum of squares principle, used to generate decompositions, can be generalized allowing for an efficient treatment of augmented linear models. The notion of the admissibility of a new variable is useful in augmenting models. Best linear unbiased estimation and tests of hypotheses can be performed through transformations and reparametrizations of the general linear model. The theory of outliers and influential observations can be generalized so as to be applicable for the general univariate

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6

Sedman, Robin. "Online Outlier Detection in Financial Time Series." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228069.

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In this Master’s thesis, diﬀerent models for outlier detection in ﬁnancial time series are examined. The ﬁnancial time series are price series such as index prices or asset prices. Outliers are, in this thesis, deﬁned as extreme and false points, but this deﬁnition is also investigated and revised. Two diﬀerent time series models are examined: an autoregressive (AR) and a generalized autoregressive conditional heteroskedastic (GARCH) time series model, as well as one test statistic method based on the GARCH model. Additionally, a nonparametric model is examined, which utilizes kernel density e

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7

Dishman, Tamarah Crouse. "Identifying Outliers in a Random Effects Model For Longitudinal Data." UNF Digital Commons, 1989. http://digitalcommons.unf.edu/etd/191.

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Identifying non-tracking individuals in a population of longitudinal data has many applications as well as complications. The analysis of longitudinal data is a special study in itself. There are several accepted methods, of those we chose a two-stage random effects model coupled with the Estimation Maximization Algorithm (E-M Algorithm) . Our project consisted of first estimating population parameters using the previously mentioned methods. The Mahalanobis distance was then used to sequentially identify and eliminate non-trackers from the population. Computer simulations were run in order to

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8

Liu, Jie. "Exploring Ways of Identifying Outliers in Spatial Point Patterns." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2528.

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This work discusses alternative methods to detect outliers in spatial point patterns. Outliers are defined based on location only and also with respect to associated variables. Throughout the thesis we discuss five case studies, three of them come from experiments with spiders and bees, and the other two are data from earthquakes in a certain region. One of the main conclusions is that when detecting outliers from the point of view of location we need to take into consideration both the degree of clustering of the events and the context of the study. When detecting outliers from the point of v

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9

Katshunga, Dominique. "Identifying outliers and influential observations in general linear regression models." Thesis, University of Cape Town, 2004. http://hdl.handle.net/11427/6772.

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Includes bibliographical references (leaves 140-149).<br>Identifying outliers and/or influential observations is a fundamental step in any statistical analysis, since their presence is likely to lead to erroneous results. Numerous measures have been proposed for detecting outliers and assessing the influence of observations on least squares regression results. Since outliers can arise in different ways, the above mentioned measures are based on motivational arguments and they are designed to measure the influence of observations on different aspects of various regression results. In what follo

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10

Giziaki, Ernestini. "Tests for uncharacteristic changes in time series data and the effects of outliers on forecasts." Thesis, London Metropolitan University, 1987. http://repository.londonmet.ac.uk/3115/.

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The thesis deals with some of the anomalies,that affect the predictive performance of univariate time series. This project should help to improve the forecasts made and should also assist those engaged in time series forecasting in real life situations in industry,government and elsewhere. The problem of testing a set of data for outliers is not new in statistics,methods having been proposed for the general linear model. However, there are very few papers on testing time series data for outliers. The greater part of the thesis is concerned with the effects of outliers on forecasts, statistical

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11

Van, Deventer Petrus Jacobus Uys. "Outliers, influential observations and robust estimation in non-linear regression analysis and discriminant analysis." Doctoral thesis, University of Cape Town, 1993. http://hdl.handle.net/11427/4363.

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12

Gustavsson, Hanna. "Clustering Based Outlier Detection for Improved Situation Awareness within Air Traffic Control." Thesis, KTH, Optimeringslära och systemteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264215.

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The aim of this thesis is to examine clustering based outlier detection algorithms on their ability to detect abnormal events in flight traffic. A nominal model is trained on a data-set containing only flights which are labeled as normal. A detection scoring function based on the nominal model is used to decide if a new and in forehand unseen data-point behaves like the nominal model or not. Due to the unknown structure of the data-set three different clustering algorithms are examined for training the nominal model, K-means, Gaussian Mixture Model and Spectral Clustering. Depending on the nom

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13

Schnepper, Teresa [Verfasser]. "Location Problems with k-max Functions - Modelling and Analysing Outliers in Center Problems / Teresa Schnepper." Wuppertal : Universitätsbibliothek Wuppertal, 2017. http://d-nb.info/1138639443/34.

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14

Schubert, Erich. "Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-166938.

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Abstract (sommario):

Knowledge Discovery in Databases (KDD) ist der Prozess, nicht-triviale Muster aus großen Datenbanken zu extrahieren, mit dem Ziel, dass diese bisher unbekannt, potentiell nützlich, statistisch fundiert und verständlich sind. Der Prozess umfasst mehrere Schritte wie die Selektion, Vorverarbeitung, Evaluierung und den Analyseschritt, der als Data-Mining bekannt ist. Eine der zentralen Aufgabenstellungen im Data-Mining ist die Ausreißererkennung, das Identifizieren von Beobachtungen, die ungewöhnlich sind und mit der Mehrzahl der Daten inkonsistent erscheinen. Solche seltene Beobachtungen können

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15

Ghawi, Christina. "Forecasting Volume of Sales During the Abnormal Time Period of COVID-19. An Investigation on How to Forecast, Where the Classical ARIMA Family of Models Fail." Thesis, KTH, Matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302396.

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During the COVID-19 pandemic, customer shopping habits have changed. Some industries experienced an abrupt shift during the pandemic outbreak while others navigate in new normal states. For some merchants, the highly-uncertain new phenomena of COVID-19 expresses as outliers in time series of volume of sales. As forecasting models tend to replicate past behavior of a series, outliers complicates the procedure of forecasting; the abnormal events tend to unreliably replicate in forecasts of the subsequent year(s). In this thesis, we investigate how to forecast volume of sales during the abnormal

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16

Paulin, Carl. "Detecting anomalies in data streams driven by ajump-diffusion process." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184230.

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Jump-diffusion processes often model financial time series as they can simulate the random jumps that they frequently exhibit. These jumps can be seen as anomalies and are essential for financial analysis and model building, making them vital to detect.The realized variation, realized bipower variation, and realized semi-variation were tested to see if one could use them to detect jumps in a jump-diffusion process and if anomaly detection algorithms can use them as features to improve their accuracy. The algorithms tested were Isolation Forest, Robust Random Cut Forest, and Isolation Forest Al

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17

Razroev, Stanislav. "AUTOMATED OPTIMAL FORECASTING OF UNIVARIATE MONITORING PROCESSES : Employing a novel optimal forecast methodology to define four classes of forecast approaches and testing them on real-life monitoring processes." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-165990.

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This work aims to explore practical one-step-ahead forecasting of structurally changing data, an unstable behaviour, that real-life data connected to human activity often exhibit. This setting can be characterized as monitoring process. Various forecast models, methods and approaches can range from being simple and computationally "cheap" to very sophisticated and computationally "expensive". Moreover, different forecast methods handle different data-patterns and structural changes differently: for some particular data types or data intervals some particular forecast methods are better than th

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18

Truran, John Maxwell. "The Teaching and Learning of Probability, with Special Reference to South Australian Schools from 1959-1994." 2001. http://hdl.handle.net/2440/37837.

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The teaching of probability in schools provides a good opportunity for examining how a new topic is integrated into a school curriculum. Furthermore, because probabilistic thinking is quite different from the deterministic thinking traditionally found in mathematics classrooms, such an examination is particularly able to highlight significant forces operating within educational practice. After six chapters which describe relevant aspects of the philosophical, cultural, and intellectual environment within which probability has been taught, a 'Broad-Spectrum Ecological Model' is developed to ex

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19

Truran, J. M. (John M. ). "The teaching and learning of probability, with special reference to South Australian schools from 1959-1994." 2001. http://web4.library.adelaide.edu.au/theses/09PH/09pht872.pdf.

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20

Wen, Zhen-Fu, and 溫振甫. "High school mathematics textbooks inquiry generic example: 99 lesson outline (a), (b) Case Volume." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/73243089709604257213.

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21

Rauch, Geraldine [Verfasser]. "The LORELIA residual test : a new outlier identification test for method comparison studies / by Geraldine Rauch." 2009. http://d-nb.info/998406295/34.

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22

Chen, Xin. "Robust second-order least squares estimation for linear regression models." Thesis, 2009. http://hdl.handle.net/1828/3087.

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The second-order least-squares estimator (SLSE), which was proposed by Wang (2003), is asymptotically more efficient than the least-squares estimator (LSE) if the third moment of the error distribution is nonzero. However, it is not robust against outliers. In this paper. we propose two robust second-order least-squares estimators (RSLSE) for linear regression models. RSLSE-I and RSLSE-II, where RSLSE-I is robust against X-outliers and RSLSE-II is robust. against X-outliers and Y-outliers. The basic idea is to choose proper weight matrices, which give a zero weight to an outlier. The RSLSEs ar

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23

Chaka, Lyson. "Impact of unbalancedness and heteroscedasticity on classic parametric significance tests of two-way fixed-effects ANOVA tests." Diss., 2016. http://hdl.handle.net/10500/23287.

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Classic parametric statistical tests, like the analysis of variance (ANOVA), are powerful tools used for comparing population means. These tests produce accurate results provided the data satisfies underlying assumptions such as homoscedasticity and balancedness, otherwise biased results are obtained. However, these assumptions are rarely satisfied in real-life. Alternative procedures must be explored. This thesis aims at investigating the impact of heteroscedasticity and unbalancedness on effect sizes in two-way fixed-effects ANOVA models. A real-life dataset, from which three different

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24

Dongmo, Jiongo Valéry. "Inférence robuste à la présence des valeurs aberrantes dans les enquêtes." Thèse, 2015. http://hdl.handle.net/1866/13720.

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Cette thèse comporte trois articles dont un est publié et deux en préparation. Le sujet central de la thèse porte sur le traitement des valeurs aberrantes représentatives dans deux aspects importants des enquêtes que sont : l’estimation des petits domaines et l’imputation en présence de non-réponse partielle. En ce qui concerne les petits domaines, les estimateurs robustes dans le cadre des modèles au niveau des unités ont été étudiés. Sinha & Rao (2009) proposent une version robuste du meilleur prédicteur linéaire sans biais empirique pour la moyenne des petits domaines. Leur estimateur

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25

Gagnon, Philippe. "Sélection de modèles robuste : régression linéaire et algorithme à sauts réversibles." Thèse, 2017. http://hdl.handle.net/1866/20583.

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