Since the middle of the twentieth century, American dance artists have presented complicated images of American identity to world audiences, as dance companies traveled abroad under the auspices of the US State Department. This dissertation uses oral history interviews, archival research, and performance analysis to investigate how dancers navigated their status as official American ambassadors in the Cold War and the years following the 2001 terrorist attacks in the US. Dance companies worked and performed in international sites, enacting messages of American democratic superiority, while individual dancers re-interpreted the contours of American identity through personal encounters with local artists and arts practices. The dancers’ memories of government-sponsored tours re-insert the American artist into American diplomatic history, prompting a reconsideration of dancers not just as diplomatic tools working to persuade global audiences, but as creative thinkers re-imagining what it means to be American. This dissertation begins in the late 1950s, as the State Department began discussing appropriate dance companies to send to the Soviet Union, as part of the performing arts initiatives that began in 1954 under the direction of President Dwight Eisenhower. The dissertation concludes by examining more recent dance in diplomacy programs initiated in 2003, coinciding with the US invasion of Iraq. My analysis considers New York City Ballet’s 1962 tour of the Soviet Union, where the company performed programs that included George Balanchine’s Serenade (1934), Agon (1957), and Western Symphony (1954), and Jerome Robbins’ Interplay (1945) during the heightened global anxieties of the Cuban Missile Crisis. My analysis of Ailey’s 1967 tour of nine African countries focuses primarily on Revelations (1960), which closed every program on the tour. Moving into the twenty-first century, I analyze A Slipping Glimpse (2007), a collaboration between Margaret Jenkins Dance Company and Tansuree Shankar Dance Company, which began as a US State Department-sponsored 2003 residency in Kolkata. To explore each tour, I consider government goals documented in archived minutes from artist selection panels; dancers’ memories of the tours, which I collected in personal interviews conducted between 2007 and 2009; and performance analysis of the pieces that traveled on each tour. / text

本論文運用Box-Jenkins 隨機時間序列模式與Winters 趨勢季節平滑模式，進行廿一 縣市液化石油氣需求預測，依模式之配合度、穩定度及預測能力予以評估上述兩種模 式之優缺點，并探討各模式於運用時之限制，以供企業界與學者運用此兩種模式之參 考。 本論文共壹冊，約為五萬餘字，分為八章，茲分述如下： 第一章：闡述研究之動機目的與方法。第二章；介紹Box-Jenkins 模型之理論與建立 方法。第三章：介紹指數平滑法之發展、種類及模式之建立方法。第四章：探討良好 預測模式所應具備之條件，以為評估之標準。第五章：運用Box-Jenkins 模式進行液 化石油氣需求模式之進立與預測。第六章：運用Winters 趨勢季節平滑模式從事液化 石油氣需求預測。第七章：比較前述兩章預測之結果。第八章：結論與建議。

<p>In recent years, two estimators have been proposed to correct the bias exhibited by the leastsquares (LS) estimator of the lagged dependent variable (LDV) coefficient in dynamic regression models when the sample is finite. They have been termed as &lsquo / mean-unbiased&rsquo / and &lsquo / medianunbiased&rsquo / estimators. Relative to other similar procedures in the literature, the two locationbased estimators have the advantage that they offer an exact and uniform methodology for LS estimation of the LDV coefficient in a first order autoregressive model with or without exogenous regressors i.e. ARX(1).</p> <p><br /> However, no attempt has been made to accurately establish and/or compare the statistical properties among these estimators, or relative to those of the LS estimator when the LDV coefficient is restricted to realistic values. Neither has there been an attempt to&nbsp / compare their performance in terms of their mean squared error (MSE) when various forms of the exogenous regressors are considered. Furthermore, only implicit confidence intervals have been given for the &lsquo / medianunbiased&rsquo / estimator. Explicit confidence bounds that are directly usable for inference are not available for either estimator. In this study a new estimator of the LDV coefficient is proposed / the &lsquo / most-probably-unbiased&rsquo / estimator. Its performance properties vis-a-vis the existing estimators are determined and compared when the parameter space of the LDV coefficient is restricted. In addition, the following new results are established: (1) an explicit computable form for the density of the LS estimator is derived for the first time and an efficient method for its numerical evaluation is proposed / (2) the exact bias, mean, median and mode of the distribution of the LS estimator are determined in three specifications of the ARX(1) model / (3) the exact variance and MSE of LS estimator is determined / (4) the standard error associated with the determination of same quantities when simulation rather than numerical integration method is used are established and the methods are compared in terms of computational time and effort / (5) an exact method of evaluating the density of the three estimators is described / (6) their exact bias, mean, variance and MSE are determined and analysed / and finally, (7) a method of obtaining the explicit exact confidence intervals from the distribution functions of the estimators is proposed.</p> <p><br /> The discussion and results show that the estimators are still biased in the usual sense: &lsquo / in expectation&rsquo / . However the bias is substantially reduced compared to that of the LS estimator. The findings are important in the specification of time-series regression models, point and interval estimation, decision theory, and simulation.</p>

<p>Drawing from the theoretical foundations of the “critical theory” of the Frankfurt School and the media ethnographic “cultural studies” approach of the british Birmingham School, this study attempts to sketch out a media theoretical overview of the contemporary state of media culture. Using the term convergence culture as the foundation, this study offers a theoretical background to the two contemporary streams that are the significant and distinct tendencies of convergence culture: intermedial convergence, its contemporary state and historical tendencies that can be traced back using the past media theoretical approach of the Frankfurt School, and cultural convergence, its contemporary state and historical tendencies, which lineage in a media theoretical context can be traced back to the british ethographic “cultural studies” field. Using contemporary drama serials to identify and pinpoint these two stream, this study shows how intermedial convergence expresses itself today through media conglomeration in terms of branding, product placement and marketing as the result of the “completed” convergence between screen culture and popular music as the current defining state of commodity culture. Using the contemporary british drama serial Doctor Who I examine the processes of meaning making among members of the television series fan culture on the popular video content page youtube.com as expressions of cultural convergence.</p><p>This study argues how the skills and talents developed in the interaction with popular culture and in a process of interaction between fans and participants (collective intelligence and participatory culture), will have an impact on the institutionalized knowledge “from above” and in a collective process will seep over to other fields of expertise. The study also argues, as a consequence of convergence culture, that in the contemporary state of online practices, social networking and in our interactions with digital media content, a mandatory “presence” has been created where we today are defined more through our online selves and these practices, than the ones that used to define us in our “physical” lives: “The medium is no longer just the message, we are living in a state where there is only messages”.</p>

Drawing from the theoretical foundations of the “critical theory” of the Frankfurt School and the media ethnographic “cultural studies” approach of the british Birmingham School, this study attempts to sketch out a media theoretical overview of the contemporary state of media culture. Using the term convergence culture as the foundation, this study offers a theoretical background to the two contemporary streams that are the significant and distinct tendencies of convergence culture: intermedial convergence, its contemporary state and historical tendencies that can be traced back using the past media theoretical approach of the Frankfurt School, and cultural convergence, its contemporary state and historical tendencies, which lineage in a media theoretical context can be traced back to the british ethographic “cultural studies” field. Using contemporary drama serials to identify and pinpoint these two stream, this study shows how intermedial convergence expresses itself today through media conglomeration in terms of branding, product placement and marketing as the result of the “completed” convergence between screen culture and popular music as the current defining state of commodity culture. Using the contemporary british drama serial Doctor Who I examine the processes of meaning making among members of the television series fan culture on the popular video content page youtube.com as expressions of cultural convergence. This study argues how the skills and talents developed in the interaction with popular culture and in a process of interaction between fans and participants (collective intelligence and participatory culture), will have an impact on the institutionalized knowledge “from above” and in a collective process will seep over to other fields of expertise. The study also argues, as a consequence of convergence culture, that in the contemporary state of online practices, social networking and in our interactions with digital media content, a mandatory “presence” has been created where we today are defined more through our online selves and these practices, than the ones that used to define us in our “physical” lives: “The medium is no longer just the message, we are living in a state where there is only messages”.

<p>In recent years, two estimators have been proposed to correct the bias exhibited by the leastsquares (LS) estimator of the lagged dependent variable (LDV) coefficient in dynamic regression models when the sample is finite. They have been termed as &lsquo / mean-unbiased&rsquo / and &lsquo / medianunbiased&rsquo / estimators. Relative to other similar procedures in the literature, the two locationbased estimators have the advantage that they offer an exact and uniform methodology for LS estimation of the LDV coefficient in a first order autoregressive model with or without exogenous regressors i.e. ARX(1).</p> <p><br /> However, no attempt has been made to accurately establish and/or compare the statistical properties among these estimators, or relative to those of the LS estimator when the LDV coefficient is restricted to realistic values. Neither has there been an attempt to&nbsp / compare their performance in terms of their mean squared error (MSE) when various forms of the exogenous regressors are considered. Furthermore, only implicit confidence intervals have been given for the &lsquo / medianunbiased&rsquo / estimator. Explicit confidence bounds that are directly usable for inference are not available for either estimator. In this study a new estimator of the LDV coefficient is proposed / the &lsquo / most-probably-unbiased&rsquo / estimator. Its performance properties vis-a-vis the existing estimators are determined and compared when the parameter space of the LDV coefficient is restricted. In addition, the following new results are established: (1) an explicit computable form for the density of the LS estimator is derived for the first time and an efficient method for its numerical evaluation is proposed / (2) the exact bias, mean, median and mode of the distribution of the LS estimator are determined in three specifications of the ARX(1) model / (3) the exact variance and MSE of LS estimator is determined / (4) the standard error associated with the determination of same quantities when simulation rather than numerical integration method is used are established and the methods are compared in terms of computational time and effort / (5) an exact method of evaluating the density of the three estimators is described / (6) their exact bias, mean, variance and MSE are determined and analysed / and finally, (7) a method of obtaining the explicit exact confidence intervals from the distribution functions of the estimators is proposed.</p> <p><br /> The discussion and results show that the estimators are still biased in the usual sense: &lsquo / in expectation&rsquo / . However the bias is substantially reduced compared to that of the LS estimator. The findings are important in the specification of time-series regression models, point and interval estimation, decision theory, and simulation.</p>

This thesis is focused on mathematical modelling of exchange rate CZK/USD in 1991 - 2014. Time series was divided into 5 parts. First Box-Jenkins methodology models were examined, especially ARIMA model. Unfortunately, the model could not be used because none of the time series showed correlation. The time series is considered as a white noise. The data appear to be completely random and unpredictable. The time series have not constant variance neither normal distribution and therefore GARCH volatility model was used as the second model. It is better not to divide time series when using model of volatility. Volatility model contributes to more accurate prediction than the standard deviation. Results were calculated in RStudio software and MS Excel.

Submitted by Yuri Barboza Cocchiarale (yuriufrj1410@hotmail.com) on 2017-07-18T13:48:06Z No. of bitstreams: 1 Dissertação FGV - Yuri Barboza 2017.pdf: 7367125 bytes, checksum: f7c2e1f50effbdca635ca98fe61d1862 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2017-07-21T14:50:15Z (GMT) No. of bitstreams: 1 Dissertação FGV - Yuri Barboza 2017.pdf: 7367125 bytes, checksum: f7c2e1f50effbdca635ca98fe61d1862 (MD5) / Made available in DSpace on 2017-07-27T12:28:16Z (GMT). No. of bitstreams: 1 Dissertação FGV - Yuri Barboza 2017.pdf: 7367125 bytes, checksum: f7c2e1f50effbdca635ca98fe61d1862 (MD5) Previous issue date: 2017-05-31 / The aim of this study is to show that the creation of the Law no. 12,858 / 2013 has an irrelevant effect in the short term, regarding issues related to health and education problems. By adopting some assumptions capable of modeling the obtained database and estimating oil production using the SARIMA, Holt-Winters and Kalman Filter models, combined with the price forecast, the portrayed results can consistently reflect the impacts brought by this law. The problem becomes even bigger in a long-term horizon, in which the migration of revenue from royalties will overwhelmingly affect the entities who benefit from it. / Este trabalho tem como objetivo mostrar que a criação da Lei n° 12.858/2013 possui um efeito irrelevante no curto prazo, no que tange as questões ligadas aos problemas da saúde e educação. Adotando algumas premissas capazes de modelar o banco de dados obtido e estimando a produção do petróleo utilizando os modelos SARIMA, Holt-Winters e Filtro de Kalman, combinadas com a previsão dos preços, os resultados apresentados conseguem refletir de forma consistente os impactos trazidos por esta lei. O problema ainda se torna maior em um horizonte de longo prazo, onde a migração da receita provida dos royalties afetará de forma devastadora os entes que se beneficiam dela.

This study uses aspects of time series methodology to model and forecast major taxes such as Personal Income Tax (PIT), Corporate Income Tax (CIT), Value Added Tax (VAT) and Total Tax Revenue(TTAXR) in the South African Revenue Service (SARS). The monthly data used for modeling tax revenues of the major taxes was drawn from January 1995 to March 2010 (in sample data) for PIT, VAT and TTAXR. Due to higher volatility and emerging negative values, the CIT monthly data was converted to quarterly data from the rst quarter of 1995 to the rst quarter of 2010. The competing ARIMA/SARIMA and Holt-Winters models were derived, and the resulting model of this study was used to forecast PIT, CIT, VAT and TTAXR for SARS fiscal years 2010/11, 2011/12 and 2012/13. The results show that both the SARIMA and Holt-Winters models perform well in modeling and forecasting PIT and VAT, however the Holt-Winters model outperformed the SARIMA model in modeling and forecasting the more volatile CIT and TTAXR. It is recommended that these methods are used in forecasting future payments, as they are precise about forecasting tax revenues, with minimal errors and fewer model revisions being necessary. / Statistics / M.Sc. (Statistics)

Magister Scientiae - MSc / In recent years, two estimators have been proposed to correct the bias exhibited by the leastsquares (LS) estimator of the lagged dependent variable (LDV) coefficient in dynamic regression models when the sample is finite. They have been termed as &lsquo;mean-unbiased&rsquo; and &lsquo;medianunbiased&rsquo; estimators. Relative to other similar procedures in the literature, the two locationbased estimators have the advantage that they offer an exact and uniform methodology for LS estimation of the LDV coefficient in a first order autoregressive model with or without exogenous regressors i.e. ARX(1). However, no attempt has been made to accurately establish and/or compare the statistical properties among these estimators, or relative to those of the LS estimator when the LDV coefficient is restricted to realistic values. Neither has there been an attempt to&nbsp; compare their performance in terms of their mean squared error (MSE) when various forms of the exogenous regressors are considered. Furthermore, only implicit confidence intervals have been given for the &lsquo;medianunbiased&rsquo; estimator. Explicit confidence bounds that are directly usable for inference are not available for either estimator. In this study a new estimator of the LDV coefficient is proposed; the &lsquo;most-probably-unbiased&rsquo; estimator. Its performance properties vis-a-vis the existing estimators are determined and compared when the parameter space of the LDV coefficient is restricted. In addition, the following new results are established: (1) an explicit computable form for the density of the LS estimator is derived for the first time and an efficient method for its numerical evaluation is proposed; (2) the exact bias, mean, median and mode of the distribution of the LS estimator are determined in three specifications of the ARX(1) model; (3) the exact variance and MSE of LS estimator is determined; (4) the standard error associated with the determination of same quantities when simulation rather than numerical integration method is used are established and the methods are compared in terms of computational time and effort; (5) an exact method of evaluating the density of the three estimators is described; (6) their exact bias, mean, variance and MSE are determined and analysed; and finally, (7) a method of obtaining the explicit exact confidence intervals from the distribution functions of the estimators is proposed. The discussion and results show that the estimators are still biased in the usual sense: &lsquo;in expectation&rsquo;. However the bias is substantially reduced compared to that of the LS estimator. The findings are important in the specification of time-series regression models, point and interval estimation, decision theory, and simulation. / South Africa