76 resultados para variance ratio
Resumo:
In an earlier paper, we adopted a bi-variate BEKK–GARCH framework and employed a systematic approach to examine structural breaks in the Hang Seng Index and Index Futures market volatility. Switching dummy variables were included and tested in the variance equations to check for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market surrounding the Asian markets crisis. In this paper, we include measures of daily trading volume from both markets in the estimation. Likelihood ratio tests indicate the switching dummy variables become insignificant and the GARCH effects diminish but remain significant. There is some evidence that the Sequential Arrival of Information Model (SIM) provides a platform to explain these market induced effects when volume of trade is accounted for.
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A class of new conjugated copolymers containing a donor (thiophene)−acceptor (2-pyran-4-ylidene-malononitrile) was synthesized via Stille coupling polymerization. The resulting copolymers were characterized by 1H NMR, elemental analysis, GPC, TGA, and DSC. UV−vis spectra indicated that the increase in the content of the thiophene units increased the interaction between the polymer main chains to cause a red-shift in the optical absorbance. Cyclic voltammetry was used to estimate the energy levels of the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO) and the band gap (Eg) of the copolymers. The basic electronic structures of the copolymers were also studied by DFT calculations with the GGA/B3LYP function. Both the experimental and the calculated results indicated an increase in the HOMO energy level with increasing the content of thiophene units, whereas the corresponding change in the LUMO energy level was much smaller. Polymer photovoltaic cells of a bulk heterojunction were fabricated with the structure of ITO/PEDOT/PSS (30 nm)/copolymer−PCBM blend (70 nm)/Ca (8 nm)/Al (140 nm). It was found that the open-circuit voltage (Voc) increased (up to 0.93 V) with a decrease in the content of thiophene units. Although the observed power convention efficiency is still relatively low (up to 0.9%), the corresponding low fill factor (0.29) indicates considerable room for further improvement in the device performance. These results provided a novel concept for developing high Voc photovoltaic cells based on donor-π-acceptor conjugated copolymers by adjusting the donor/acceptor ratio.
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This study investigates the determinants of the fertility rate in Taiwan over the period 1966–2001. Consistent with theory, the key explanatory variables in Taiwan's fertility model are real income, infant mortality rate, female education and female labor force participation rate. The test for cointegration is based on the recently developed bounds testing procedure while the long-run and short-run elasticities are based on the autoregressive distributed lag model. Among our key results, female education and female labor force participation rate are found to be the key determinants of fertility in Taiwan in the long run. The variance decom-position analysis indicates that in the long run approximately 45percent of the variation in fertility is explained by the combined impact of female labor force participation, mortality and income, implying that socioeconomic development played an important role in the fertility transition in Taiwan. This result is consistent with the traditional structural hypothesis.
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Objectives. To compare body mass index (BMI), waist circumference and waist–hip ratio (WHR) as indices of obesity and assess the respective associations with type 2 diabetes, hypertension and dyslipidaemia.
Design and setting. A national sample of 11 247 Australians aged ≥25 years was examined in 2000 in a cross-sectional survey.
Main outcome measures. The examination included a fasting blood sample, standard 2-h 75-g oral glucose tolerance test, blood pressure measurements and questionnaires to assess treatment for dyslipidaemia and hypertension. BMI, waist circumference and WHR were measured to assess overweight and obesity.
Results. The prevalence of obesity amongst Australian adults defined by BMI, waist circumference and WHR was 20.8, 30.5 and 15.8% respectively. The unadjusted odds ratio for the fourth vs. first quartile of each obesity measurement showed that WHR had the strongest relationship with type 2 diabetes, dyslipidaemia (women only) and hypertension. Following adjustment for age, however, there was little difference between the three measures of obesity, with the possible exceptions of hypertension in women, where BMI had a stronger association, and dyslipidaemia in women and type 2 diabetes in men, where WHR was marginally superior.
Conclusions. Waist circumference, BMI and WHR identified different proportions of the population, as measured by both prevalence of obesity and cardiovascular disease (CVD) risk factors. Whilst WHR had the strongest correlations with CVD risk factors before adjustment for age, the three obesity measures performed similarly after adjustment for age. Given the difficulty of using age-adjusted associations in the clinical setting, these results suggest that given appropriate cut-off points, WHR is the most useful measure of obesity to use to identify individuals with CVD risk factors.
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One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.
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This note provides a distribution-based justification for the ratio form of contest success functions (CSFs), in which a player’s success depends positively on her effort relative to that of her opponents. I show that the inverse exponential distribution of the random shocks yields the ratio form. Extending this approach to asymmetric contests, I also derive an asymmetric ratio form of CSFs.
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Background :
The correlations between systolic blood pressure (SBP) and total cholesterol levels (CHOL) might result from genetic or environmental factors that determine variation in the phenotypes and are shared by family members. Based on 330 nuclear families in the Framingham Heart Study, we used a multivariate normal model, implemented in the software FISHER, to estimate genetic and shared environmental components of variation and genetic and shared environmental correlation between the phenotypes. The natural logarithm of the phenotypes measured at the last visit in both Cohort 1 and 2 was used in the analyses. The antihypertensive treatment effect was corrected before adjustment of the systolic blood pressure for age, sex, and cohort.
Results :
The univariate correlation coefficient was statistically significant for sibling pairs and parent-offspring pairs, but not significant for spouse pairs. In the bivariate analysis, the cross-trait correlation coefficients were not statistically significant for all relative pairs. The shared environmental correlation was statistically significant, but the genetic correlation was not significant.
Conclusion :
There is no significant evidence for a close genetic correlation between systolic blood pressure and total cholesterol levels. However, some shared environmental factors may determine the variation of both phenotypes.
Resumo:
Most cases of {alpha}-thalassemia result from large deletions at the {alpha}-globin locus (1). The {alpha}-globin gene cluster contains a tandem array of 2 nearly identical {alpha}-globin genes (HBA; Fig. 1A ) (2). The {alpha}0-thalassemias are characterized by deletions that inactivate both {alpha}-globin genes of a given chromosome, whereas in {alpha}+-thalassemias, one gene remains functional. The most widespread {alpha}+-thalassemias are those designated –{alpha}3.7 and –{alpha}4.2, according to the lengths of the deleted fragments (3).
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Little grassbirds (Megalurus gramineus) are small, sexually monomorphic passerines that live in reed beds, lignum swamps and salt marshes in southern Australia. The breeding biology and patterns of sex allocation of the little grassbird were investigated over a single breeding season. Our observations of this species in the Edithvale Wetland Reserve revealed a highly male-biased population sex ratio, with some breeding territories containing several additional males. Nevertheless, there was little compelling evidence that little grassbirds breed cooperatively. The growth rates of male and female nestlings were similar and, as predicted by theory, there was no overall primary sex ratio bias. However, the primary sex ratio was female-biased early in the breeding season and became increasingly male-biased later in the breeding season.
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The aim of the present study was to examine quantitative differences in lobar cerebral cortical volumes in a healthy adult population. Quantitative volumetric MRI of whole brain, cerebral and cerebellar volumes was performed in a cross-sectional analysis of 97 normal volunteers, with segmented frontal, temporal, parietal and occipital cortical volumes measured in a subgroup of 60 subjects, 30 male and 30 female, matched for age and sex. The right cerebral hemisphere was larger than the left across the study group with a small (<1%) but significant difference in symmetry (P < 0.001). No difference was found between volumes of right and left cerebellar hemispheres. Rightward cerebral cortical asymmetry (right larger than left) was found to be significant across all lobes except parietal. Males had greater cerebral, cerebellar and cerebral cortical lobar volumes than females. Larger male cerebral cortical volumes were seen in all lobes except for left parietal. Females had greater left parietal to left cerebral hemisphere and smaller left temporal to left cerebral hemisphere ratios. There was a mild reduction in cerebral volumes with age, more marked in males. This study confirms and augments past work indicating underlying structural asymmetries in the human brain, and provides further evidence that brain structures in humans are differentially sensitive to the effects of both age and sex.
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The 3rd generation partnership project (3GPP) long term evolution (LTE) standard uses single carrier frequency division multiple access (SCFDMA) scheme for the uplink transmissions and orthogonal frequency division multiplexing access (OFDMA) in downlink. SCFDMA uses DFT spreading prior to OFDMA modulation to map the signal from each user to a subset of the available subcarriers i.e., single carrier modulation. The efficiency of a power amplifier is determined by the peak to average power ratio (PAPR) of the modulated signal. In this paper, we analyze the PAPR in 3GPP LTE systems using root raised cosine based filter. Simulation results show that the SCFDMA subcarrier mapping has a significantly lower PAPR compared to OFDMA. Also comparing the three forms of SCFDMA subcarrier mapping, results show that interleave FDMA (IFDMA) subcarrier mapping with proposed root raised cosine filter reduced PAPR significantly than localized FDMA (LFDMA) and distributed (DFDMA) mapping. This improves its radio frequency (RF) power amplifier efficiency and also the mean power output from a battery driven mobile terminal.
Resumo:
Purpose - The purpose of this paper is to analyse the interdependencies of the house price growth rates in Australian capital cities.
Design/methodology/approach - A vector autoregression model and variance decomposition are introduced to estimate and interpret the interdependences among the growth rates of regional house prices in Australia.
Findings - The results suggest the eight capital cities can be divided into three groups: Sydney and Melbourne; Canberra, Adelaide and Brisbane; and Hobart, Perth and Darwin.
Originality/value - Based on the structural vector autoregression model, this research develops an innovative interdependence analysis approach of regional house prices based on a variance decomposition method.
Resumo:
This paper utilizes a methodological approach called Multi-Level Modeling (MLM) that addresses two major shortcomings in the two step analytic process that is traditionally adopted in the pertinent literature for modeling corporate collapse; thereby, enhancing procedural efficiency. The robustness of MLM vis-à-vis the traditional two-step procedure is ascertained using a data sample of Australian
publicly listed companies, equally split between collapsed and non collapsed, during the period 1989 to 2006. The results indicate that not only does MLM improve procedural efficiency, it does so while
enhancing the robustness of signaling corporate collapse; in particular, MLM signals collapse with an overall 6.6% increase in accuracy.
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Background/Objectives: There is variability in the association between dietary intake and health outcomes across different countries, especially among the elderly. We used the gold standard dietary assessment method, a weighed food record, to examine the association between dietary pattern and mortality in a representative sample of community dwelling participants from Great Britain aged 65 years and older.
Subjects/Methods: Dietary intake was recorded at baseline in 1017 elderly participants (520 men, 497 women, mean age 76.3±7.4 years). Exploratory factor analysis was performed to examine dietary patterns and participants were followed up over an average of 9.2 years for mortality.
Results: The factor analysis revealed four interpretable principal components accounting for approximately 9.8% of the total variance, with similar patterns across sex. A ‘Mediterranean-style’ dietary pattern explained the greatest proportion of the variance (3.7%), followed by ‘health-aware’ (2.2%), ‘traditional’ (2.0%) and ‘sweet and fat’ (1.9%) factors. There were a total of 683 deaths through follow-up. After adjustment for potential confounders, only the Mediterranean-style dietary pattern remained associated with mortality (highest vs lowest tertile; hazard ratio¼0.82, 95% CI, 0.68–1.00). The benefits of the Mediterranean-style diet were only observed among women (hazard ratio¼0.71, 95% CI 0.52–0.96) although in men the traditional diet was a risk factor for mortality (hazard ratio¼1.30, 95% CI 1.00–1.71).
Conclusions: Using a gold standard approach, our results confirm previous evidence that dietary patterns are important in longevity among the elderly.