Academic literature on the topic 'Pooled mean group estimation'
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Journal articles on the topic "Pooled mean group estimation"
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Blackburne, Edward F., and Mark W. Frank. "Estimation of Nonstationary Heterogeneous Panels." Stata Journal: Promoting communications on statistics and Stata 7, no. 2 (June 2007): 197–208. http://dx.doi.org/10.1177/1536867x0700700204.
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We introduce a new Stata command, xtpmg, for estimating nonstationary heterogeneous panels in which the number of groups and number of time-series observations are both large. Based on recent advances in the nonstationary panel literature, xtpmg provides three alternative estimators: a traditional fixed-effects estimator, the mean-group estimator of Pesaran and Smith (Estimating long-run relationships from dynamic heterogeneous panels, Journal of Econometrics 68: 79–113), and the pooled mean-group estimator of Pesaran, Shin, and Smith (Estimating long-run relationships in dynamic heterogeneous panels, DAE Working Papers Amalgamated Series 9721; Pooled mean group estimation of dynamic heterogeneous panels, Journal of the American Statistical Association 94: 621–634).
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Pesaran, M. Hashem, Yongcheol Shin, and Ron P. Smith. "Pooled Mean Group Estimation of Dynamic Heterogeneous Panels." Journal of the American Statistical Association 94, no. 446 (June 1999): 621–34. http://dx.doi.org/10.1080/01621459.1999.10474156.
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Ullah, Saif, and Masood Sarwar Awan. "Environmental Kuznets Curve and Income Inequality: Pooled Mean Group Estimation for Asian Developing Countries." Forman Journal of Economic Studies 15 (December 30, 2019): 157–79. http://dx.doi.org/10.32368/fjes.20191507.
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Bangake, Chrysost, and Jude C. Eggoh. "Pooled Mean Group estimation on international capital mobility in African countries." Research in Economics 66, no. 1 (March 2012): 7–17. http://dx.doi.org/10.1016/j.rie.2011.06.001.
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Martı́nez-Zarzoso, Inmaculada, and Aurelia Bengochea-Morancho. "Pooled mean group estimation of an environmental Kuznets curve for CO2." Economics Letters 82, no. 1 (January 2004): 121–26. http://dx.doi.org/10.1016/j.econlet.2003.07.008.
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Guan, Long-Fei, and Wee-Yeap Lau. "Triffin Dilemma and International Monetary System : Evidence from Pooled Mean Group Estimation." Journal of Asian Finance, Economics and Business 5, no. 2 (May 31, 2018): 5–14. http://dx.doi.org/10.13106/jafeb.2018.vol5.no2.5.
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Zaman, Khalid, Basheer M. Al-Ghazali, Aqeel Khan, Arieff Salleh Bin Rosman, S. Sriyanto, Sanil S. Hishan, and Zainudin Abu Bakar. "Pooled Mean Group Estimation for Growth, Inequality, and Poverty Triangle: Evidence from 124 Countries." Journal of Poverty 24, no. 3 (October 31, 2019): 222–40. http://dx.doi.org/10.1080/10875549.2019.1678553.
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Keho, Yaya. "Impact of Budget Deficit on Private Consumption inWAEMU Countries: Evidence from Pooled Mean Group Estimation." International Journal of Economics and Finance 8, no. 3 (February 26, 2016): 189. http://dx.doi.org/10.5539/ijef.v8n3p189.
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This study empirically investigates the impact of budget deficit on private consumption in seven member countries of the West African Economic and Monetary Union (WAEMU), namely Benin, Burkina Faso, Côte d’Ivoire, Mali, Niger, Senegal and Togo. It applies the pooled mean group estimation method to annual data covering the period 1970 to 2013. The results show that budget deficit and per capita GDP have long run positive effects on household consumption whereas inflation rate is detrimental to private consumption. This suggests that private consumption cannot be held responsible for any crowding-out effects that budget deficit might have on long run aggregate demand and economic growth in WAEMU countries. Therefore, restricting the size of budget deficits is costly for the development of WAEMU countries.
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Seraphin, Prao Yao. "Urbanization, Gender and Economic Growth in the Waemu Zone: Evidence from Pooled Mean Group Estimation." Advances in Politics and Economics 3, no. 4 (December 1, 2020): p47. http://dx.doi.org/10.22158/ape.v3n4p47.
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This study empirically analyses the influence of urbanization and the participation of men and women in the labour force on economic growth in the countries of the West African Economic and Monetary Union (WAEMU). Using data from the World Bank (2017) on the member States between 1990 and 2016, we show from Pesaran’s PMG estimator, Shin and Smith (1999) that in the short term, youth and women are very useful for economic growth. In the long term, urbanization, industrial added value and the elderly make a positive contribution to economic growth. The study urges governments to create better living conditions by ensuring adequate income levels and care, i.e., public policies should aim to increase employment, establish or improve social protection, social integration, health and the fight against discrimination.
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Khan, Hameed, Umair Khan, Li Jun Jiang, and Muhamad Asif Khan. "Impact of infrastructure on economic growth in South Asia: Evidence from pooled mean group estimation." Electricity Journal 33, no. 5 (June 2020): 106735. http://dx.doi.org/10.1016/j.tej.2020.106735.
Full textDissertations / Theses on the topic "Pooled mean group estimation"
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Samargandi, Nahla. "Essays on financial development and economic growth." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11071.
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This thesis is based on three empirical essays in financial development and economic growth. The first essay, investigated in the third chapter, the effect of financial development on economic growth in the context of Saudi Arabia, an oil-rich economy. In doing so, the study distinguishes between the effects of financial development on the oil and non-oil sectors of the economy. The Autoregressive Distributed Lag (ARDL) bounds test methodology is applied to yearly data over the period 1968 to 2010. The finding of this study is that financial development has a positive impact on the growth of the non-oil sector. In contrast, its impact on the oil-sector growth and total GDP growth is either negative or insignificant. This suggests that the relationship between financial development and growth may be fundamentally different in resource-dominated economies. The second essay revisited, in the fourth chapter, the relationship between financial development and economic growth in a panel of 52 middle-income countries over the 1980-2008 period. Using pooled mean group estimations in a dynamic heterogeneous panel setting, we show that there is an inverted U-shaped relationship between finance and growth in the long-run. In the short run, the relationship is insignificant. This suggests that too much finance can exert a negative influence on growth in middle-income countries. The finding of a non-monotonic effect of financial development on growth is confirmed by estimating a dynamic panel threshold model. The third essay empirically explores cross-country evidence of the effects of financial development shocks on economic growth. It employs a Global Vector Autoregressive (GVAR) model, which allows us to capture the dynamics of this relationship in a multi-country setting, and connects countries through bilateral international trade. Given the progressive role that Brazil, Russia, India, China and South Africa (BRICS) play in the world economic arena, this essay focuses on whether financial development in one BRICS member state affects economic growth in the other BRICS. To this end, the study finds empirical evidence that credit to the private sector has a positive spillover effect on growth in some of the BRICS countries. However, the results imply that the current level of financial integration among the BRICS countries is still not mature enough to spur economic growth for all the BRICS members.
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Diallo, Ibrahima Amadou. "Exchange rates policy and productivity." Thesis, Clermont-Ferrand 1, 2013. http://www.theses.fr/2013CLF10405/document.
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Cette thèse étudie comment le taux de change effectif réel (TCER) et ses mesures associées (volatilité du TCER et désalignement du TCER) affectent la croissance de la productivité totale des facteurs (CPTF). Elle analyse également les canaux par lesquels le TCER et ses mesures associées agissent sur la productivité totale des facteurs (PTF). La première partie étudie comment le TCER lui-Même, d'une part, et la volatilité du TCER, d'autre part, influencent la productivité. Une analyse du lien entre le niveau du TCER et la PTF dans le chapitre 1 indique qu'une appréciation de taux de change cause une augmentation de la PTF. Mais cet impact est également non- inéaire: en-Dessous du seuil, le TCER influence négativement la productivité tandis qu'au-Dessus du seuil il agit positivement. Les résultats du chapitre 2 illustrent que la volatilité du TCER affecte négativement la CPTF. Nous avons également constaté que la volatilité du TCER agit sur PTF selon le niveau du développement financier. Pour les pays modérément financièrement développés, la volatilité du TCER réagit négativement sur la productivité et n'a aucun effet sur la productivité pour les niveaux très bas et très élevés du développement financier. La deuxième partie examine les canaux par lesquels le TCER et ses mesures associées influencent la productivité. Les résultats du chapitre 3 illustrent que la volatilité du TCER a un impact négatif élevé sur l'investissement. Ces résultats sont robustes dans les pays à faible revenu et les pays à revenu moyens, et en employant une mesure alternative de volatilité du TCER. Le chapitre 4 montre que le désalignement du taux de change réel et la volatilité du taux de change réel affectent négativement les exportations. Il démontre également que la volatilité du taux de change réel est plus nocive aux exportations que le désalignement. Ces résultats sont corroborés par des résultats sur des sous-Échantillons de pays à bas revenu et à revenu moyenThis dissertation investigates how the real effective exchange rate (REER) and its associated asurements (REER volatility and REER misalignment) affect total factor productivity growth (TFPG). It also analyzes the channels through which the REER and its associated measurements act on total factor productivity (TFP). The first part studies how the REER itself, on the one hand, and the REER volatility, on the other hand, influence productivity. An analysis of the link between the level of REER and TFP in chapter 1 reveals that an exchange rate appreciation causes an increase of TFP. But this impact is also nonlinear: below the threshold, real exchange rate influences negatively productivity while above the threshold it acts positively. The results of chapter 2 illustrate that REER volatility affects negatively TFPG. We also found that REER volatility acts on TFP according to the level of financial development. For moderately financially developed countries, REER volatility reacts negatively on productivity and has no effect on productivity for very low and very high levels of financial development. The second part examines the channels through which the REER and its associated measurements influence productivity. The results of chapter 3 illustrate that the exchange rate volatility has a strong negative impact on investment. This outcome is robust in low income and middle income countries, and by using an alternative measurement of exchange rate volatility. Chapter 4 show that both real exchange rate misalignment and real exchange rate volatility affect negatively exports. It also demonstrates that real exchange rate volatility is more harmful to exports than misalignment. These outcomes are corroborated by estimations on subsamples of Low- ncome and Middle-Income countries
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Svedberg, Stefan. "The impact of fossil and non-fossil energy consumption on economic growth : -Evidence from a pooled mean group analysis." Thesis, Umeå universitet, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172393.
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This paper investigates the causal relationship between economic growth and fossil and nonfossil energy consumption while controlling for human and physical capital in a panel of 74 countries over 1990 to 2017. The global sample was divided into four categories according to the World Bank income classifications: low-income, lower-middle income, upper-middle income, and high-income. The purpose of the income level subsamples was to further analyze the role of the country’s income level in the nexus between energy consumption and economic growth. This paper uses panel unit root and cross-sectional independence testing and employs the Pooled Mean Group estimator. The main results in this paper reveal (1) bidirectional causality between fossil energy consumption and economic growth for the low income and lower-middle income countries; (2) unidirectional causality from economic growth to fossil energy consumption for the high income and upper-middle income countries. In terms of nonfossil energy consumption, the results are more mixed; there is (3) unidirectional causality from economic growth to non-fossil energy consumption for the low-income and upper-middle income countries; (4) bidirectional causality between non-fossil energy consumption and economic growth for the lower-middle income countries; and (5) unidirectional causality from non-fossil energy consumption to economic growth for the high-income countries. These results have several policy implications that are discussed.
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Diallo, Ibrahima Amadou. "EXCHANGE RATE POLICY AND PRODUCTIVITY." Phd thesis, Université d'Auvergne - Clermont-Ferrand I, 2013. http://tel.archives-ouvertes.fr/tel-00997038.
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Cette thèse étudie comment le taux de change effectif réel (TCER) et ses mesures associées (volatilité du TCER et désalignement du TCER) affectent la croissance de la productivité totale des facteurs (CPTF). Elle analyse également les canaux par lesquels le TCER et ses mesures associées agissent sur la productivité totale des facteurs (PTF). La première partie étudie comment le TCER lui-même, d'une part, et la volatilité du TCER, d'autre part, influencent la productivité. Une analyse du lien entre le niveau du TCER et la PTF dans le chapitre 1 indique qu'une appréciation de taux de change cause une augmentation de la PTF. Mais cet impact est également non-linéaire: en-dessous du seuil, le TCER influence négativement la productivité tandis qu'au-dessus du seuil il agit positivement. Les résultats du chapitre 2 illustrent que la volatilité du TCER affecte négativement la CPTF. Nous avons également constaté que la volatilité du TCER agit sur PTF selon le niveau du développement financier. Pour les pays modérément financièrement développés, la volatilité du TCER réagit négativement sur la productivité et n'a aucun effet sur la productivité pour les niveaux très bas et très élevés du développement financier. La deuxième partie examine les canaux par lesquels le TCER et ses mesures associées influencent la productivité. Les résultats du chapitre 3 illustrent que la volatilité du TCER a un impact négatif élevé sur l'investissement. Ces résultats sont robustes dans les pays à faible revenu et les pays à revenu moyens, et en employant une mesure alternative de volatilité du TCER. Le chapitre 4 montre que le désalignement du taux de change réel et la volatilité du taux de change réel affectent négativement les exportations. Il démontre également que la volatilité du taux de change réel est plus nocive aux exportations que le désalignement. Ces résultats sont corroborés par des résultats sur des sous-échantillons de pays à bas revenu et à revenu moyen.
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Mirková, Barbora. "Promítání měnového kurzu ve střední a východní Evropě." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-339142.
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This thesis examines the exchange rate pass-through into consumer prices in Central and Eastern Europe. The study is based on quarterly data of 12 countries from 2003 to 2013. Estimations are conducted using heterogeneous panel cointegration methods, namely the mean group and the pooled mean group estimators. Fixed effects are used as a reference. The thesis provides short- run and long-run estimates of the exchange rate pass-through for the individual countries and for the region as a whole. Based on the results, we conclude that the exchange rate pass-through is highly variable across Central and Eastern Europe. We find that there is no clear distinction between the pass-through rates in euro area countries, EU countries not using the euro and non- EU countries. Further, we find that the generally accepted concept of higher exchange rate pass- though in developing countries does not hold in this region. JEL Classification C23, E31, E52, F31 Keywords exchange rate pass-through, pooled mean group, mean group, heterogeneous panel cointegration Author's e-mail bara.mirkova@centrum.cz Supervisor's e-mail roman.horvath@gmail.com
Book chapters on the topic "Pooled mean group estimation"
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Tsukuma, Hisayuki, and Tatsuya Kubokawa. "Multivariate Linear Model and Group Invariance." In Shrinkage Estimation for Mean and Covariance Matrices, 27–33. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1596-5_4.
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van Eeden, Constance, and James V. Zidek. "Group Bayes Estimation of the Exponential Mean: A Retrospective View of the Wald Theory." In Statistical Decision Theory and Related Topics V, 35–49. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2618-5_3.
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Purczyński, Jan. "Estimation of the Mean Velocity of a Group of Vehicles in Strong Random Noise Conditions." In Communications in Computer and Information Science, 168–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16472-9_18.
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Adams, Samuel, and Eric Evans Osei Opoku. "Population Growth and Urbanization in Africa." In Population Growth and Rapid Urbanization in the Developing World, 282–97. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0187-9.ch014.
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This study examined the effect of population growth and urbanization on the environment (carbon dioxide emissions) for 37 sub Saharan African countries based on 1980-2010 annual data. Using the Pooled Mean Group estimation technique, the findings of the study show that affluence and industrialization have negative effect on the environment (increases carbon dioxide emissions) while urbanization does not have a significant effect on carbon dioxide emissions. The population variable is significant only in the long run but insignificant in the short run. Also, after controlling for the different age groups, the results show that the more active age group (15-59) is positive and significantly related to carbon dioxide emissions.
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Adams, Samuel, and Eric Evans Osei Opoku. "Population Growth and Urbanization in Africa." In Socio-Economic Development, 1355–70. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7311-1.ch069.
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This study examined the effect of population growth and urbanization on the environment (carbon dioxide emissions) for 37 sub Saharan African countries based on 1980-2010 annual data. Using the Pooled Mean Group estimation technique, the findings of the study show that affluence and industrialization have negative effect on the environment (increases carbon dioxide emissions) while urbanization does not have a significant effect on carbon dioxide emissions. The population variable is significant only in the long run but insignificant in the short run. Also, after controlling for the different age groups, the results show that the more active age group (15-59) is positive and significantly related to carbon dioxide emissions.
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Alper, Fındık Özlem, and Ali Eren Alper. "Causal Interactions Between Foreign Direct Investments, Trade, and Economic Growth." In Advances in Finance, Accounting, and Economics, 242–64. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7564-1.ch014.
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The main objective of this chapter is to detect the impacts of FDI and foreign trade on the economic growth of middle income countries. Therefore, this study aims to examine the relationship among economic growth, foreign direct investments, and trade in 27 middle-income countries according to the United Nations (UN) classification through panel data analysis method. According to the results of the Pedroni cointegration test, the null hypothesis suggesting no cointegration among the series at 1% significance level is rejected in all seven tests. According to pooled mean group estimator estimation results, the coefficients of foreign direct investment and trade which have long-term impacts on economic growth are also identified. Accordingly, the coefficients of both variables are statistically significant. A 1% increase in foreign direct investment and trade increase economic growth by 0.24% and 0.02%, respectively.
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Megaravalli, Amith Vikram. "Macroeconomics and Its Impact on Stock Markets of India, China, and Japan." In Behavioral Finance and Decision-Making Models, 177–94. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7399-9.ch010.
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The objective of this chapter is to examine the long-run and the short-run relationship between India, China, and Japanese stock markets and key macroeconomic variables such as exchange rates and inflation (proxied by consumer price index) of ASIAN 3 economies (India, China, and Japan). Monthly time series data spanning the period from 2008 January to November 2016 has been used. The unit root test, the cointegration test, Granger causality test, and pooled mean group estimator have been applied to derive the long-run and short-run statistical dynamics. The findings of pooled estimated results of ASIAN 3 countries show that exchange rate has a positive and significant long-run effect on stock markets while the inflation has a negative and insignificant long-run effect. In the short run, there is no statistically significant relationship between macroeconomic variables and stock markets. This study emphasizes the impact of macroeconomic variables on the stock market performance of a developing economy (India and China) and developed economy (Japan).
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Garidzirai, Rufaro. "An Analysis of Economic Determinants and Crime in Selected Gauteng Local Municipalities." In Standard of Living, Wellbeing, and Community Development [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96339.
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The relationship between macroeconomic objectives and crime is intertwined and cannot be overemphasized. This subject has created an endless debate and at the centre of this debate is what causes the other? In contributing to this academic debate, the current study investigates the impact of macroeconomic objectives on crime. Furthermore, the study examined the question “what causes the other?”. In achieving these two aims, the study employed a Pooled Mean Group and the Granger Causality analysis from 1996–2019. The Pooled Mean Group results reveal that poverty and inequality are the main causes of crime in the Gauteng province. On the other hand, economic growth, education and employment reduces crime. Since Gauteng is the economic harbor of Africa, many jobs should be created therein to reduce poverty and inequality that have a negative impact on crime.
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Hankin, David G., Michael S. Mohr, and Ken B. Newman. "Stratified sampling." In Sampling Theory, 68–91. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.003.0005.
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In stratified sampling, the N population units are grouped into L strata, independent samples are selected from within each stratum, and unbiased estimation is achieved as a weighted average of stratum-specific estimates. Strata may be natural—pool, riffle, and run habitat unit types in a small stream—or strata may be constructed to ensure that some units from specific groups of population units will always be included in the sample. Within strata, any unbiased method of selection can be used. If SRS is used within strata, this is a stratified SRS design. Allocation of the total stratified sample of size n across the L strata can affect sampling variance of stratified estimators. Optimal allocation theory shows that optimal stratum-specific sample sizes depend on relative numbers of units in strata, and stratum-specific costs per unit of sampling and variances of y values. An ANOVA sums of squares partition can be used to show that a proportionally allocated stratified SRS strategy will outperform selection of a single SRS with mean-per-unit estimation whenever the average variation within strata is less than the finite population variance. Therefore, it is desirable to minimize variation within strata and maximize the variation in stratum means. For a variety of reasons, post-stratification, in which one large SRS is stratified after the sample has been selected, may often be a good alternative to selection of a (pre-) stratified sample.
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Penman, Alan D., Kimberly W. Crowder, and William M. Watkins. "Pooled Data Analysis of the Ahmed Baerveldt Comparison Study and the Ahmed Versus Baerveldt Study." In 50 Studies Every Ophthalmologist Should Know, 109–14. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780190050726.003.0019.
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Data from 2 independent randomized clinical trials, the Ahmed Baerveldt Comparison (ABC) Study and the Ahmed Versus Baerveldt (AVB) Study, were pooled for analysis to determine whether the Ahmed-FP7 or the Baerveldt BG101-350 implant was more efficacious in the treatment of refractory or high-risk glaucoma. Both devices lowered intraocular pressure (IOP) and decreased the need for glaucoma medications. The Baerveldt group had a lower failure rate, lower rate of de novo glaucoma surgery, and lower mean IOP on fewer medications than the Ahmed group. However, Baerveldt implantation carried a higher risk of hypotony. The authors recommended that the selection of a device for a patient should be based on target IOP, compliance with medications, urgency for IOP lowering, surgeon familiarity with each device, and the surgeon’s personal outcomes with the individual devices.
Conference papers on the topic "Pooled mean group estimation"
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Kandlikar, Satish G. "A Scale Analysis Based Theoretical Force Balance Model for Critical Heat Flux (CHF) During Saturated Flow Boiling in Microchannels and Minichannels." In ASME 2009 Second International Conference on Micro/Nanoscale Heat and Mass Transfer. ASMEDC, 2009. http://dx.doi.org/10.1115/mnhmt2009-18549.
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Accurate prediction of critical heat flux (CHF) in microchannels and small diameter tubes is of great interest in estimating the safe operational limits of cooling systems employing flow boiling. Scale analysis is applied to identify the relevant forces leading to the CHF condition. Using these forces, a local parameter model is developed to predict the flow boiling CHF. The theoretical model is an extension of an earlier pool boiling CHF model incorporating a force balance among the evaporation momentum, surface tension, inertia, and viscous forces. Weber number, capillary number, and a new non-dimensional group K2, representing the ratio of evaporation momentum to surface tension forces, emerged as main groups in quantifying the narrow channel effects on CHF. The constants in the model were calculated from the available experimental data. The mean error with ten data sets is 19.7 percent, with 76 percent data falling within ±30% error band, and 93 percent within ±50% error band. Evaluating individualized set of constants for each data set resulted in mean errors of less than 10 percent for all data sets. The success of the model indicates that flow boiling CHF can be modeled as a local phenomenon and the scale analysis is able to reveal important information regarding fundamental mechanisms leading to the CHF condition. The final equations resulting from this model are given by Eqs. (18–22) along with the transition criteria given by Eq. (28).
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Toulon, P., C. Jacquot, M. O. Frydman, D. Vignon, and M. Aiach. "ANTITHROMBIN III AND HEPARIN COFACTOR II IN PATIENTS WITH CHRONIC RENAL FAILURE." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644359.
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Anti thrombin III (AT III) and heparin cofactor II (HC II) were measured in 77 blood donors, 82 patients with chronic renal failure (CRF) undergoing regular hemodialysis and 36 undialyzed patients with CRF. AT III was measured as heparin cofactor and HC II as dermatan sulfate cofactor using amidolytic assays.The results (mean ± SD expressed in percentage of the in pooled normal plasma) are summurized in the table.Subnormal AT III levels were found in both dialyzed and undialyzed patients with CRF, while HC II was significantly (p < 0.001) reduced in dialyzed patients (12 of them were found to have HC II levels below to lowest value founded in our control group: 68 %).In order to explain this decrease of HC II level in dialyzed patients with CRF, we compared both AT III and HC II activities before and after a dialysis session in 24 patients (12 with a low and 12 with normal before dialysis HC II activity). AT III and HC II increased significantly (p < 0.01) in all patients after dialysis. When related to total plasma proteins in order to suppress the influence of hemoconcentration induced by dialysis, AT III decreased significantly (p < 0.01) in the 24 patients while HC II increased significantly (p < 0.01) only in patients with low before dialysis HC II levels (the increase in HC II activity was found significantly in the pooled 24 patients).
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Gonchikar, Ugrasen, Holalu Venkatdas Ravindra, Rudreshi Addamani, and Prathik Jain Sudhir. "Estimation and Comparison of Machining Performances Using Group Method Data Handling Technique and ANN in Wire EDM of Stavax Material." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23435.
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Abstract Wire Electrical Discharge Machining (WEDM) is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. This study outlines the development of model and its application to estimation of machining performances using Group Method Data Handling Technique (GMDH) and Artificial Neural Network (ANN). Experimentation was performed as per Taguchi’s L’16 orthogonal array for Stavax (modified AISI 420 steel) material. Each experiment has been performed under different cutting conditions of pulse-on, pulse-off, current and bed speed. Among different process parameters voltage and flush rate were kept constant. Molybdenum wire having diameter of 0.18 mm was used as an electrode. Four responses namely accuracy, surface roughness, Volumetric Material Removal Rate (VMRR) and Electrode Wear (EW) have been considered for each experiment. Estimation and comparison of responses was carried out using GMDH and ANN. Group method data handling technique is ideal for complex, unstructured systems where the investigator is only interested in obtaining a high-order input-output relationship. Also, the method is heuristic in nature and is not based on a solid foundation as in regression analysis. The GMDH algorithm is designed to learn the process by training the algorithm with the experimental data. The experimental observations are divided into two sets viz., the training set and testing set. The training set is used to make the GMDH learn the process and the testing set will check the performance of GMDH. Different models can be obtained by varying the percentage of data in the training set and the best model can be selected from these, viz., 50%, 62.5% & 75%. The best model is selected from the said percentages of data. Number of variables selected at each layer is usually taken as a fixed number or a constantly increasing number. It is usually given as fractional increase in number of independent variables present in the previous level. Three different criterion functions, viz., Root Mean Square (Regularity) criterion, Unbiased criterion and Combined criterion were considered for estimation. The choice of the criterion for node selection is another important parameter for proper modeling. The Artificial Neural Network is used to study and predict the machining responses. Input data are fed into the neural network and corresponding weights and bias are extracted. Then weights and bias are integrated in the program which is used to calculate and predict the machining responses. Estimation of machining performances was obtained by using ANN for various cutting conditions. ANN estimates were obtained for various percentages of total data in the training set viz., 50%, 60% & 70%. The best model is selected from the said percentages of data. Estimation and comparison of machining performances were carried out using GMDH and ANN. Estimates from GMDH and ANN were compared and it was observed that ANN with 70% of data in training set gives better results than GMDH.
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Heeb, M. J., D. F. Mosher, and J. H. Griffin. "PROTEIN C IS ACTIVATED AND GIVES 110,000 MW COMPLEXES AND PROTEIN S IS CLEAVED AND DECREASED _IN VIVO IN PATIENTS WITH INTRAVASCULAR COAGULATION (DIC)." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644696.
Full textAbstract:
Immunoblotting studies using denaturing and nondenaturing polyacrylamide gel electrophoresis conditions were performed on 100 plasmas from 88 patients with suspected DIC, in order to determine whether the anticoagulant regulatory proteins C and S (PC and PS) cure altered in vivo during DIC. 70 of these plasmas from 65 patients contained 5-35% of PC antigen in the form of activated protein C (APC) complexed with inhibitor(s).24 normal plasmas showed no detectable APC-inhibitor complexes.The complexes in DIC plasmas had a MW of 110 K on SDS-PAGE, as did complexes formed when APC was incubated with plasma immunodepleted of PC, or when PC in normal plasma was activated with Protac C. On nondenaturing gels, the complex present in 69 of 70 patient plasmas had the same mobility as one of two major bands of complexed APC observed in Protac C-activated normal plasma. One patient plasma contained two forms of PC antigen complex. This patient had suffered a perforated uterus during an abortion. After Protac C activation of the patient plasmas, two APC complexed bands were seen. The 16 patients with >15% complexed PC antigen included 3 with severe infection, 5 with solid tumors, 3 with leukemias, 2 with vascular disease and 3 with other diagnoses. These patients had a higher mortality (69%) than the group as a whole and higher levels of fibrin degradation products. 13 of these 16 plasmas and 56 of the entire group of 100 contained a higher than normal proportion of PS in a cleaved form with an apparent molecular weight lower than intact PS on reduced SDS-PAGE. Mean levels of PS antigen determined by electroimmunoassay for 95 of the plasmas were as follows: entire group, 86% (92%); patients with infection (n=34), 76% (81%); patients with malignancy (n=37), 102% (105%); all others (n=24), 70% (74%) wherfe numbers in parentheses exclude patients with liver disease and 100% normal pooled plasma. These studies suggest that PS is cleaved and decreased in vivo and that PC is activated in vivo and complexed with a 50K MW inhibitor(s) during DIC.
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Bonnaffoux, Guillaume, and Cécile Melis. "Alternative Method for Estimation of Design Extremes for Moored Floaters." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-23832.
Full textAbstract:
After having relied for decades totally on small scale model tests, the design of anchoring systems for moored floaters like FPSOs is now widely performed numerically. Estimation of design maxima during mooring analyses requires calculating system response for a large number of sea states in order to screen all possible scenarios between wind, waves and current parameters. In addition, the slow-drift response motions of the system constituted by the floater and the anchoring system are highly dependent of the wave elevation realization, which is not an input parameter of the simulations and can lead to extremely variable responses. This is generally addressed by designers by performing the analysis for the same sea state and varying the wave group spectrum (or wave components phases) a large number of times N (20–50 realizations is a typical range, see Refs [4], [5]). For these N realizations, N response maxima are extracted, and a distribution of response extremes is derived, from which the response level is extracted. In terms of computational cost, performing N 3-hour simulations to derive N values of extreme response is extremely expensive. The paper will focus on methods that can be employed to reduce the computational cost of analyses. In a first step, the rapidity of statistical convergence of response estimates depending on the system will be investigated. This will allow pre-determining the number of sea states realizations required to reach a satisfactory convergence of response. In a second step, a mean of improving the computational efficiency of calculations carried-out to reach the statistical convergence will be proposed.
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Jain Sudhir, Prathik, Ravindra Holalu Venkatadas, Naveen Prakash Goravi Vijaya Dev, and Ugrasen Gonchikar. "Estimation and Comparison of Acoustic Emission Parameters and Surface Roughness in Wire Cut Electric Discharge Machining of Stavax Material Using Multiple Regression Analysis and Group Method Data Handling Technique." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50596.
Full textAbstract:
Wire Electrical Discharge Machining (WEDM) is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. Selection of cutting parameters for obtaining higher cutting efficiency or accuracy in WEDM is still not fully solved, even with most up-to-date CNC WEDM machine. It is widely recognised that Acoustic Emission (AE) is gaining ground as a monitoring method for health diagnosis on rotating machinery. The advantage of AE monitoring over vibration monitoring is that the AE monitoring can detect the growth of subsurface cracks whereas the vibration monitoring can detect defects only when they appear on the surface. This study outlines the estimation of AE parameters viz., signal strength, absolute energy, RMS in the WEDM. Stavax (modified AISI 420) steel material was machined using different process parameters based on Taguchi’s L’16 standard orthogonal array. Among different process parameters voltage and flush rate were kept constant. Parameters such as pulse-on time, pulse-off time, current and bed speed was varied. Molybdenum wire having diameter of 0.18 mm was used as an electrode. Simple functional relationships between the parameters were plotted to arrive at possible information on surface roughness and AE signals. But these simpler methods of analysis did not provide any information about the status of the work material. Thus, there is a requirement for more sophisticated methods that are capable of integrating information from the multiple sensors. Hence, methods like Multiple Regression Analysis (MRA) and Group Method of Data Handling (GMDH) have been applied for the estimation of surface roughness, AE signal strength, AE absolute energy and AE RMS. The GMDH algorithm is designed to learn the process by training the algorithm with the experimental data. The experimental observations are divided into two sets: the training set and testing set. The training set is used to make the GMDH learn the process and the testing set will check the performance of GMDH. Different models can be obtained by varying the percentage of data in the training set and the best model can be selected from these, viz., 50%, 62.5% and 75%. The best model is selected from the said percentages of data. Number of variables selected at each layer is usually taken as a fixed number or a constantly increasing number. It is usually given as fractional increase in number of independent variables present in the previous level. Three different criterion functions, viz., Root Mean Square (Regularity) criterion, Unbiased criterion and Combined criterion were considered for the estimation. The choice of criterion for node selection is another important parameter for proper modeling. From the results it was observed that, AE parameters and estimated surface roughness values were correlates well with GMDH when compare to MRA.
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Destek, Mehmet Akif, Müge Manga, and Neşe Algan. "Investigation on the Validity of Natural Resource Curse Hypothesis in Gulf Cooperation Council Countries." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c09.01979.
Full textAbstract:
This study aims to investigate the validity of natural resource curse hypothesis in Gulf Cooperation Council (GCC) countries for the period from 1980 to 2014. In doing so, the relationship between real GDP, natural resource abundance, financial development and gross fixed capital is examined using with second generation panel data methodology which allows to cross-sectional dependence among countries. In case of mean group estimation, it is concluded that natural resource rents, financial development and capital positively affects the real GDP in GCC countries. However, in case of individual country estimations, we found that natural resource curse hypothesis is valid only in United Arab Emirates.
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Gonchikar, Ugrasen, Ravindra Holalu Venkatadas, Naveen Prakash Goravi Vijaya Dev, Keshavamurthy Ramaiah, and Giridhara Gudekota. "Comparison of Machining Performances in Wire EDM for HCHCr Material Using Group Method Data Handling Technique and Artificial Neural Network." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50588.
Full textAbstract:
Wire Electrical Discharge Machining (WEDM) is a specialized thermo electrical machining process capable of accurately machining parts with varying hardness or complex shapes. Present study outlines the comparison of machining performances in the wire electric discharge machining using group method data handling technique and artificial neural network. HCHCr material was selected as a work material. This work material was machined using different process parameters based on Taguchi’s L27 standard orthogonal array. Parameters such as pulse-on time, pulse-off time, current and bed speed were varied. The response variables measured for the analysis are surface roughness, volumetric material removal rate and dimensional error. Machining performances were compared using sophisticated mathematical models viz., Group Method of Data Handling (GMDH) technique and Artificial Neural Network (ANN). GMDH is ideal for complex, unstructured systems where the investigator is only interested in obtaining a high-order input-output relationship. Also, the method is heuristic in nature and is not based on a solid foundation as regression analysis. The GMDH algorithm is designed to learn the process by training the algorithm with the experimental data. The experimental observations are divided into two sets viz., the training set and testing set. The training set is used to make the GMDH learn the process and the testing set will check the performance of GMDH. Different models were obtained by varying the percentage of data in the training set and the best model were selected from these, viz., 50%, 62.5% & 75%. The best model was selected from the said percentages of data. Number of variables selected at each layer is usually taken as a fixed number or a constantly increasing number. It is usually given as fractional increase in number of independent variables present in the previous level. Three different criterion functions, viz., Root Mean Square (Regularity) criterion, Unbiased criterion and Combined criterion were considered for estimation. The choice of the criterion for node selection is another important parameter for proper modeling. The Artificial Neural Network is used to study and predict the machining responses. Input data are fed into the neural network and corresponding weights and bias are extracted. Then weights and bias are integrated in the program which is used to calculate and predict the machining responses. Estimation of machining performances was obtained by using ANN for various cutting conditions. ANN estimates were obtained for various percentages of total data in the training set viz., 50%, 60% & 70%. The best model was selected from the said percentages of data. Estimation and comparison of machining performances were carried out using GMDH and ANN. Estimates from GMDH and ANN were compared and it was observed that ANN with 70% of data in training set gives better results than GMDH.
Reports on the topic "Pooled mean group estimation"
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Tarko, Andrew P., Mario Romero, Cristhian Lizarazo, and Paul Pineda. Statistical Analysis of Safety Improvements and Integration into Project Design Process. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317121.
Full textAbstract:
RoadHAT is a tool developed by the Center for Road Safety and implemented for the INDOT safety management practice to help identify both safety needs and relevant road improvements. This study has modified the tool to facilitate a quick and convenient comparison of various design alternatives in the preliminary design stage for scoping small and medium safety-improvement projects. The modified RoadHAT 4D incorporates a statistical estimation of the Crash Reduction Factors based on a before-and-after analysis of multiple treated and control sites with EB correction for the regression-to-mean effect. The new version also includes the updated Safety Performance Functions, revised average costs of crashes, and the comprehensive table of Crash Modification Factors—all updated to reflect current Indiana conditions. The documentation includes updated Guidelines for Roadway Safety Improvements. The improved tool will be implemented at a sequence of workshops for the final end users and preceded with a beta-testing phase involving a small group of INDOT engineers.