1,720,997 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Generalizations Of Chebyshev's Inequality
No full textU ovom diplomskom radu napravljen je pregled generalizacija Čebiševljeve nejednakosti. Na početku su obrađene klasične Čebiševljeva i Markovljeva nejednakost, a zatim su prikazane njihove generalizacije, koje su razvrstane u tri skupine. Prvaskupinaobuhvaćanejednakostivezaneuzjednuslučajnuvarijablu,poput Pearsonove, Selbergove, Cantellijeve i Gaussove nejednakosti. Druga skupina odnosi se na nejednakosti za sumu nezavisnih slučajnih varijabli, koje mogu biti jednako distribuirane (primjerice Guttmanova nejednakost), ali i ne moraju (kao što su Bernsteinova, Birnbaum-Raymond-Zuckermanova i Kolmogorovljeva nejednakost). Treća skupina obuhvaća nejednakosti vezane uz slučajne vektore, kao što su Bergeova i multivarijatne Čebiševljeve nejednakosti. Za većinu prikazanih nejednakosti provedenaje usporedbanjihoveoštrinesodgovarajućomČebiševljevomnejednakošću te je dan primjer njihove primjene u konkretnim problemskim situacijama iz stvarnog svijeta.This paper provides an overview of generalizations of Chebyshev’s inequality. It begins with presenting the classical Chebyshevand Markovine qualities,followed by their generalizations, which are categorized into three groups. The first group includes inequalities related to a single random variable, such as Pearson’s, Selberg’s, Cantelli’s, and Gauss’s inequalities. The second groupfocuses oninequalities for the sumofindependentrandomvariables,whichmaybeidenticallydistributed (e.g., Guttman’s inequality) or not (e.g., Bernstein’s, Birnbaum-RaymondZuckerman’s, and Kolmogorov’s inequalities). The third group covers inequalities related to random vectors, such as Berge’s inequality and multivariate versions of Chebyshev’s inequality. For most of the presented inequalities, a comparison o ftheirs harpness with the corresponding Chebyshev inequality is conducted, along with illustrative examples of their application in real-world situations
Quantitative Risk Measures And Portfolio Performance Measures
No full textRazvojem brojnih online platformi za trgovanje na burzama razvila se i potreba za praćenjem mjera rizika i mjera performansi portfelja. U financijskom svijetu važno je znati kvantificirati rizik i odrediti performanse svoga portfelja što je upravo i ideja
ovoga rada. Kako bismo razumjeli suvremene mjere rizika potrebno je upoznati se i sa starijim mjerama. Upoznavanje mjera performansi i mjera rizika uvelike nam olakšava donošenje odluka vezanih uz ulaganje, ali pri tumačenju mjera moramo
biti izrazito oprezni i poznavati ograničenja koja nam se nameću sa svakom od navedenih mjera. Kako je trenutno u praksi najzastupljenija mjera rizika vrijednost pod rizikom (VaR) tako smo se najviše fokusirali na definiranje i primjere vezane
uz navedenu mjeru rizika. Kako vrijednost pod rizikom ima svoja ograničenja tako se u povijesti razvila potreba za varijacijom vrijednosti pod rizikom i te su na taj način nastale mjere rizika poput prosječne vrijednosti pod rizikom, inkrementalne
vrijednosti pod rizikom i komponente vrijednosti pod rizikom koje smo definirali i uz pomoć primjera objasnili.
Mjerama performanse portfelja također se pridaje velika važnost kod ulagača. Među mjerama performanse portfelja prvo smo naveli Sharpeov i Treynorov omjer koji su i povijesno bili preteča novim mjerama performanse portfelja. Naposljetku smo se
pozabavili Sortino omjerom i alfom koji su trenutno u uporabi u brojim financijskim institucijama.With the development of numerous online trading platforms, the need has also developed for monitoring risk measures and portfolio performance measures. In the financial world it is important to know how to quantify risk and determine
the performance of your portfolio which is the idea of this work. To understand modern risk measures it is necessary to become familiar with the older measures. Getting to know performance measures and risk measures makes it much easier
for us to make investment-related decisions, but we have to be very careful when interpreting the measures and know the limitations that are imposed on us with each of the mentioned measures. As the Value at Risk (VaR) is currently the most
common measure of risk in practice, we focused mostly on defining and examples related to the specified risk measure. As Value at risk has its limitations, thus the need for variation has developed. This is how risk measures such as the average
values at risk, incremental values at risk and components value at risk were created. Portfolio performance measures are also highly valued by investors. Among the portfolio performance measures, we first listed the Sharpe and Treynor ratios, which
historically were the forerunners of new portfolio performance measures. Finally, we tackled the Sortino ratio and the alpha that are currently in use in many financial institution
Quantitative Risk Measures And Portfolio Performance Measures
No full textRazvojem brojnih online platformi za trgovanje na burzama razvila se i potreba za praćenjem mjera rizika i mjera performansi portfelja. U financijskom svijetu važno je znati kvantificirati rizik i odrediti performanse svoga portfelja što je upravo i ideja
ovoga rada. Kako bismo razumjeli suvremene mjere rizika potrebno je upoznati se i sa starijim mjerama. Upoznavanje mjera performansi i mjera rizika uvelike nam olakšava donošenje odluka vezanih uz ulaganje, ali pri tumačenju mjera moramo
biti izrazito oprezni i poznavati ograničenja koja nam se nameću sa svakom od navedenih mjera. Kako je trenutno u praksi najzastupljenija mjera rizika vrijednost pod rizikom (VaR) tako smo se najviše fokusirali na definiranje i primjere vezane
uz navedenu mjeru rizika. Kako vrijednost pod rizikom ima svoja ograničenja tako se u povijesti razvila potreba za varijacijom vrijednosti pod rizikom i te su na taj način nastale mjere rizika poput prosječne vrijednosti pod rizikom, inkrementalne
vrijednosti pod rizikom i komponente vrijednosti pod rizikom koje smo definirali i uz pomoć primjera objasnili.
Mjerama performanse portfelja također se pridaje velika važnost kod ulagača. Među mjerama performanse portfelja prvo smo naveli Sharpeov i Treynorov omjer koji su i povijesno bili preteča novim mjerama performanse portfelja. Naposljetku smo se
pozabavili Sortino omjerom i alfom koji su trenutno u uporabi u brojim financijskim institucijama.With the development of numerous online trading platforms, the need has also developed for monitoring risk measures and portfolio performance measures. In the financial world it is important to know how to quantify risk and determine
the performance of your portfolio which is the idea of this work. To understand modern risk measures it is necessary to become familiar with the older measures. Getting to know performance measures and risk measures makes it much easier
for us to make investment-related decisions, but we have to be very careful when interpreting the measures and know the limitations that are imposed on us with each of the mentioned measures. As the Value at Risk (VaR) is currently the most
common measure of risk in practice, we focused mostly on defining and examples related to the specified risk measure. As Value at risk has its limitations, thus the need for variation has developed. This is how risk measures such as the average
values at risk, incremental values at risk and components value at risk were created. Portfolio performance measures are also highly valued by investors. Among the portfolio performance measures, we first listed the Sharpe and Treynor ratios, which
historically were the forerunners of new portfolio performance measures. Finally, we tackled the Sortino ratio and the alpha that are currently in use in many financial institution
Exponential Distribution
No full textU ovom radu smo imali cilj opisati i objasniti eksponencijalnu distribuciju, njena svojstva, povezanost s ostalim distribucijama i upotrebu u stvarnom životu. Prisjetit ćemo se nekih osnovnih definicija iz teorije vjerojatnosti, a zatim ćemo definirati funkciju gustoće eksponencijalne distribucije, te izvesti funkciju distribucije, očekivanje i varijancu za eksponencijalnu distribuciju. Nakon toga obraditi ćemo svojstva eksponencijalne distribucije medu kojima je vrlo bitno svojstvo odsustva memorije koje ćemo i dokazati. Analizirat ćemo povezanost eksponencijalne distribucije s Laplaceovom i s Paretovom distribucijom te napraviti izvod za njihove funkcije distribucije.In this paper we had a goal to closely examine and explain very interesting exponential distribution, it’s properties and uses in real life. We will discuss it’s density function, distribution, expected value and variance. Next we will define and prove very important memoryless property and also define some others properties of exponential distribution which we will not prove. In last chapter we will talk about connection between the Laplace and Pareto distributions and exponential distribution
Numerical Characteristics of Random Variables
No full textTema ovog rada su numeričke karakteristike slučajnih varijabli. Za potrebe njihovog definiranja, bilo je potrebno ponoviti osnovne pojmove i iskazati najvažnije rezultate iz teorije vjerojatnosti. Na osnovu slike slučajne varijable, promatrane su dvije vrste slučajnih
varijabli - diskretna i neprekidna slučajna varijabla. Kako se definiranje numeričkih karakteristika razlikuje za te dvije varijable, prvo su definirane numeričke karakteristike za diskretnu slučajnu varijablu, reprezentirani su primjeri određivanja tih karakteristika, a zatim je bilo navedeno kako se računaju neke od osnovnih numeričkih karakteristika za neke od najvažnijih parametarskih distribucija. Zatim, analogno je prikazano sve navedeno za slučaj neprekidnih slučajnih varijabli. Dodatno, prikazan je tablični prikaz numeričkih karakteristika za neke od poznatijih parametarskih diskretnih i neprekidnih distribucija. U posljednjem poglavlju
objašnjena je i na primjerima prikazana interpretacija numeričkih karakteristika slučajne varijable.The topic of this bachelor’s thesis is numerical characteristics of random variables. For the purpose of defining them, it was necessary to repeat the basic concepts and express the most important results from probability theory. Based on the image of a random variable, two types of random variables were observed - discrete and continuous random variables. As the definition of numerical characteristics differs for these two types, firstly were defined numerical characteristics for a discrete random variable, examples of determining these characteristics were presented, and then some of the basic numerical characteristics for some of the most important parametric distributions were calculated. Analogously everything stated was shown for the case of continuous random variables. Additionally, a tabular presentation of many numerical characteristics for some of the most important parametric discrete and continuous distributions is presented. In the last chapter, the interpretation of
the numerical characteristics of a random variable is explained and shown with examples
Estimators In Parametric Models
No full textTema ovog rada su procjenitelji u parametarskim statističkim modelima. Za potrebe razumijevanja definirani su osnovni pojmovi iz teorije vjerojatnosti i statistike, iskazani su najbitniji rezultati te su navedeni primjeri parametarski zadanih distribucija. Pomoću uvedenih pojmova definiran je procjenitelj i neka njegova svojstva koja su poželjna te su definirani procjenitelji očekivanja, varijance i proporcije jednostavnog slučajnog uzorka. Iz navedenih primjera prametarski zadanih distribucija proizašli su konkretni parametarski statistički modeli. Za svaki navedeni parametarski statistički model napravljena je analiza, odnosno definiran je procjenitelj traženog parametra te su komentirana svojstva procjenitelja. Također, napravljene su simulacije koje ilustriraju spomenuta svojstva.The topic of this bachelor’s thesis are estimators of parameters in parametric models. Firstly, we defined some of the basic concepts and presented the most important results from the probability theory and statistics. Also, we presented examples of special probability distributions. The estimator and some of its desirable properties, and the estimators of expectation,
variance and proportion of a random sample were defined using introduced terms. For each listed parametric distribution we defined parametric statistical model and an estimator of the required parameter. The properties of the estimator were analysed. Also, there are simulations which illustrate the mentioned properties
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