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Using Multivariate Statistics

The goal of therapy for bradycardia or tachycardia is to rapidly identify and treat patients who are hemodynamically unstable or symptomatic due to the arrhythmia. Drugs or, when appropriate, pacing may be used to control unstable or symptomatic bradycardia. Cardioversion or drugs or both may be used to control unstable or symptomatic tachycardia. ACLS providers should closely monitor stable patients pending expert consultation and should be prepared to aggressively treat those with evidence of decompensation.

/pdf/part-8-adult-advanced-cardiovascular-life-support-2010-344vtppnij.pdf

Part 8: Adult Advanced Cardiovascular Life Support 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)

/pdf/nonlinear-time-series-analysis-1j3a35n4y3.pdf

Nonlinear Time Series Analysis.

Thank you very much for reading input output analysis foundations and extensions. As you may know, people have search hundreds times for their chosen readings like this input output analysis foundations and extensions, but end up in infectious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some malicious virus inside their desktop computer.

Input Output Analysis Foundations And Extensions

Comparing financial systems.

We analyze the European transition economics and show that many time series of major indices exhibit (i) power-law correlations in their values, (ii) power-law correlations in their magnitudes and (iii) an asymmetric probability distribution. Applying the phase randomization procedure to these time series, we show that magnitude correlations completely vanish. We propose a stochastic model that can generate time series with features (i), (ii) and (iii), and we show by means of numerical simulations that this model is capable of reproducing these three features found in the empirical data.

https://polymer.bu.edu/hes/articles/pfjgs06.pdf

Fractionally integrated process for transition economics

In this paper, a wavelet analysis of long-range dependence (LRD) based on the Hurst exponent is presented. An estimator is used to perform an analysis of LRD in the capital markets of six transition economies. The results suggest that we can divide the stock markets into two groups: markets with strong LRD (the Czech Republic, Hungary, Russia, and Slovenia), and markets with no or only a weak form of LRD (Poland and Slovakia). Additionally, if the Hurst exponent is estimated on a sliding time window, the results show some additional properties, which we believe are representative for the markets in transition economies.

/pdf/does-the-efficient-market-hypothesis-hold-evidence-from-six-28kv8xemkz.pdf

Does the Efficient Market Hypothesis Hold?: Evidence from Six Transition Economies

In this paper, we studied cyclical patterns in a transition economy. We introduced a dynamic perspective into the analysis by applying multivariate wavelet analysis. The wavelet covariance and wavelet correlation were defined and applied to the analysis of business cycles as an alternative to the traditional cross-spectrum analysis. The main findings indicated that there is a significant business cycle component in aggregate economic activity and that business cycles are asymmetric and highly synchronized with the EU cycle. Additionally, it was found that three distinctive periods of business cycle synchronization exert an important impact on the properties of a business cycle.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1746-1049.2004.tb01015.x

Method of analyzing business cycles in a transition economy: the case of slovenia

The development of a stock market depends to a great extent on the development of institutional investors. The paper studies the mutual fund industry and applies various tests to evaluate the performance capacity of mutual funds. First, we briefly explain the data, and then we introduce the performance measures used to evaluate funds. Finally, we calculate the performance measures of mutual funds and rank them according to the results. We find the rankings obtained by performing both the Sharpe and Treynor rules to be almost the same, implying that funds are well diversified. The rankings reveal that all analyzed funds outperformed the market on a risk-adjusted basis.

/pdf/risk-adjusted-performance-of-mutual-funds-some-tests-g6ycvmsv91.pdf

Risk-adjusted performance of mutual funds: some tests

Optimized spiral spherical self-organizing map is applied to real-life dataWe investigate the European Union banking sector in the 2000-2011 periodWe use micro and macro economic data for two separate modelsBoth models reveal the existence of two separate banking clustersDynamic analysis indicates intensification of integration within the two groups The paper presents a comprehensive treatment of the European Union banking sector in the 2000-2011 period A wide set of economic indicators is used to derive two-level approach: micro and macro topologies We use the methodology of the optimized spiral spherical self-organizing map, a version of Kohonen's Self-Organizing Maps, which overcomes some of the major deficiencies found in standard methods In dynamic analysis we recover the path of the integration process itself by calculating the dynamics of the countries around the sphere and by examining the measure of dispersion The simultaneous comparison of the micro and macro levels provides deeper insights into the banking sector integration process Both models, the micro and macro, unveil the formation of two banking clusters, which, with the exception for Greece, coincides with a division between new and old member states Both clusters intensify integration within their cluster

Timotej Jagric

Papers

Fractionally integrated process for transition economics

Does the Efficient Market Hypothesis Hold?: Evidence from Six Transition Economies

Method of analyzing business cycles in a transition economy: the case of slovenia

Risk-adjusted performance of mutual funds: some tests

Optimized spiral spherical self-organizing map approach to sector analysis - The case of banking