Efficient Estimation of Copula-based Semiparametric Markov Models

This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant (one-dimensional marginal) distributions and parametric bivariate copula functions; where the copulas capture temporal dependence and tail dependence of the processes. The Markov processes generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student's $t$ copulas and their survival copulas are all geometrically ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We show that the sieve MLEs of any smooth functionals are root-$n$ consistent, asymptotically normal and efficient; and that their sieve likelihood ratio statistics are asymptotically chi-square distributed. We present Monte Carlo studies to compare the finite sample performance of the sieve MLE, the two-step estimator of Chen and Fan (2006), the correctly specified parametric MLE and the incorrectly specified parametric MLE. The simulation results indicate that our sieve MLEs perform very well; having much smaller biases and smaller variances than the two-step estimator for Markov models generated via Clayton, Gumbel and other tail dependent copulas.Copula, Tail dependence, Nonlinear Markov models, Geometric ergodicity, Sieve MLE, Semiparametric efficiency, Sieve likelihood ratio statistics, Value-at-Risk

Analysis on relationship between extreme pathways and correlated reaction sets

Background: Constraint-based modeling of reconstructed genome-scale metabolic networks has been successfully applied on several microorganisms. In constraint-based modeling, in order to characterize all allowable phenotypes, network-based pathways, such as extreme pathways and elementary flux modes, are defined. However, as the scale of metabolic network rises, the number of extreme pathways and elementary flux modes increases exponentially. Uniform random sampling solves this problem to some extent to study the contents of the available phenotypes. After uniform random sampling, correlated reaction sets can be identified by the dependencies between reactions derived from sample phenotypes. In this paper, we study the relationship between extreme pathways and correlated reaction sets.Results: Correlated reaction sets are identified for E. coli core, red blood cell and Saccharomyces cerevisiae metabolic networks respectively. All extreme pathways are enumerated for the former two metabolic networks. As for Saccharomyces cerevisiae metabolic network, because of the large scale, we get a set of extreme pathways by sampling the whole extreme pathway space. In most cases, an extreme pathway covers a correlated reaction set in an \u27all or none\u27 manner, which means either all reactions in a correlated reaction set or none is used by some extreme pathway. In rare cases, besides the \u27all or none\u27 manner, a correlated reaction set may be fully covered by combination of a few extreme pathways with related function, which may bring redundancy and flexibility to improve the survivability of a cell. In a word, extreme pathways show strong complementary relationship on usage of reactions in the same correlated reaction set.Conclusion: Both extreme pathways and correlated reaction sets are derived from the topology information of metabolic networks. The strong relationship between correlated reaction sets and extreme pathways suggests a possible mechanism: as a controllable unit, an extreme pathway is regulated by its corresponding correlated reaction sets, and a correlated reaction set is further regulated by the organism\u27s regulatory network.<br /

CD4+ and CD8+ T cells have opposing roles in breast cancer progression and outcome

The Cancer Immunoediting concept has provided critical insights suggesting dual functions of immune system during the cancer initiation and development. However, the dynamics and roles of CD4(+) and CD8(+) T cells in the pathogenesis of breast cancer remain unclear. Here we utilized two murine breast cancer models (4T1 and E0771) and demonstrated that both CD4(+) and CD8(+) T cells were increased and involved in immune responses, but with distinct dynamic trends in breast cancer development. In addition to cell number increases, CD4(+) T cells changed their dominant subsets from Th1 in the early stages to Treg and Th17 cells in the late stages of the cancer progression. We also analyzed CD4(+) and CD8(+) T cell infiltration in primary breast cancer tissues from cancer patients. We observed that CD8(+) T cells are the key effector cell population mediating effective anti-tumor immunity resulting in better clinical outcomes. In contrast, intra-tumoral CD4(+) T cells have negative prognostic effects on breast cancer patient outcomes. These studies indicate that CD4(+) and CD8(+) T cells have opposing roles in breast cancer progression and outcomes, which provides new insights relevant for the development of effective cancer immunotherapeutic approaches

Semiparametric estimation of the bid-ask spread in extended roll models

We propose new methods for estimating the bid-ask spread from observed transaction prices alone. Our methods are based on the empirical characteristic function. We compare our methods theoretically and numerically with the Roll (1984) method as well as with its best known competitor, the Hasbrouck (2004) method, and find that our estimators perform much better when this distribution is far from Gaussian. Our methods are applied to the E-mini futures con- tract on the S&P 500 during the Flash Crash of May 6, 2010. We also establish √T consistency and asymptotic normality of the proposed estimators in various extended Roll models.non

Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models

This paper considers estimation of semi-nonparametric GARCH filtered copula models in which the individual time series are modelled by semi-nonparametric GARCH and the joint distributions of the multivariate standardized innovations are characterized by parametric copulas with nonparametric marginal distributions. The models extend those of Chen and Fan (2006) to allow for semi-nonparametric conditional means and volatilities, which are estimated via the method of sieves such as splines. The fitted residuals are then used to estimate the copula parameters and the marginal densities of the standardized innovations jointly via the sieve maximum likelihood (SML). We show that, even using nonparametrically filtered data, both our SML and the two-step copula estimator of Chen and Fan (2006) are still root-n consistent and asymptotically normal, and the asymptotic variances of both estimators do not depend on the nonparametric filtering errors. Even more surprisingly, our SML copula estimator using the filtered data achieves the full semiparametric efficiency bound as if the standardized innovations were directly observed. These nice properties lead to simple and more accurate estimation of Value-at-Risk (VaR) for multivariate financial data with flexible dynamics, contemporaneous tail dependence and asymmetric distributions of innovations. Monte Carlo studies demonstrate that our SML estimators of the copula parameters and the marginal distributions of the standardized innovations have smaller variances and smaller mean squared errors compared to those of the two-step estimators in finite samples. A real data application is presented

Relaxation of the one child policy and trends in caesarean section rates and birth outcomes in China between 2012 and 2016: observational study of nearly seven million health facility births.

OBJECTIVE: To examine how the relaxation of the one child policy and policies to reduce caesarean section rates might have affected trends over time in caesarean section rates and perinatal and pregnancy related mortality in China. DESIGN: Observational study. SETTING: China's National Maternal Near Miss Surveillance System (NMNMSS). PARTICIPANTS: 6 838 582 births at 28 completed weeks or more of gestation or birth weight ≥1000 g in 438 hospitals in the NMNMSS between 2012 and 2016. MAIN OUTCOME MEASURES: Obstetric risk was defined using a modified Robson classification. The main outcome measures were changes in parity and age distributions and relative frequency of each Robson group, crude and adjusted trends over time in caesarean section rates within each risk category (using Poisson regression with a robust variance estimator), and trends in perinatal and pregnancy related mortality over time. RESULTS: Caesarean section rates declined steadily between 2012 and 2016 (crude relative risk 0.91, 95% confidence interval 0.89 to 0.93), reaching an overall hospital based rate of 41.1% in 2016. The relaxation of the one child policy was associated with an increase in the proportion of multiparous births (from 34.1% in 2012 to 46.7% in 2016), and births in women with a uterine scar nearly doubled (from 9.8% to 17.7% of all births). Taking account of these changes, the decline in caesarean sections was amplified over time (adjusted relative risk 0.82, 95% confidence interval 0.81 to 0.84). Caesarean sections declined noticeably in nulliparous women (0.75, 0.73 to 0.77) but also declined in multiparous women without a uterine scar (0.65, 0.62 to 0.77). The decrease in caesarean section rates was most pronounced in hospitals with the highest rates in 2012, consistent with the government's policy of targeting hospitals with the highest rates. Perinatal mortality declined from 10.1 to 7.2 per 1000 births over the same period (0.87, 0.83 to 0.91), and there was no change in pregnancy related mortality over time. CONCLUSIONS: China is the only country that has succeeded in reverting the rising trends in caesarean sections. China's success is remarkable given that the changes in obstetric risk associated with the relaxation of the one child policy would have led to an increase in the need for caesarean sections. China's experience suggests that change is possible when strategies are comprehensive and deal with the system level factors that underpin overuse as well as the various incentives at work during a clinical encounter

Efficient estimation of copula-based semiparametric Markov models

This paper considers the efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant (one-dimensional marginal) distributions and parametric bivariate copula functions where the copulas capture temporal dependence and tail dependence of the processes. The Markov processes generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student's $t$ copulas and their survival copulas are all geometrically ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We show that the sieve MLEs of any smooth functional is root-$n$ consistent, asymptotically normal and efficient and that their sieve likelihood ratio statistics are asymptotically chi-square distributed. Monte Carlo studies indicate that, even for Markov models generated via tail dependent copulas and fat-tailed marginals, our sieve MLEs perform very well.Comment: Published in at http://dx.doi.org/10.1214/09-AOS719 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Understanding IS Success Model and Valence Framework in Sellers’ Acceptance of Cross-border E-commerce

Cross-border e-commerce becomes more and more popular and general. The foci of researches in e-commerce have moved from domestic towards to global market. Yet, most of extant literatures are from buyer’s perspective, whereas sellers are also important in the success of cross-border e-commerce. In this study, we are aiming to identify the elements of the success of cross-border e-commerce and the relationship with trust and intention to use from seller’s perspective. To do so, we apply a mixed method to accomplish this research. We have identified the key factors which sellers are concerned about, and why they engage in cross-border e-commerce. In addition, we have developed new dimensions with associated items for system quality, service quality, perceived benefit and perceived cost in the context of cross-border e-commerce. The theoretical contributions and practical contributions have been discussed lastly

Mathematical and experimental evaluation of a mini-channel PV/T and thermal panel in summer mode

In this paper, a mini-channel PV/T and mini-channel thermal panel hot water system is presented. The thermal panels in this system use mini-channel tube as the heat exchanger, which has a small hydraulic diameter and large heat exchanger area, and this special structure can improve the heat transfer coefficient at the same flow rate than the conventional type. The performance of this system for generating hot water and electricity in summer has been tested, and a simulation model of this operating mode has been developed. Based on a typical day's weather data, the simulation model is verified, and the experimental and simulated results agree with each other very well. The results reveal that the experimental and simulated electrical efficiencies of PV/T panels are 11.5% and 12.6%, respectively. The experimental and simulated thermal efficiencies of thermal collectors are 46.8% and 48.0%, respectively. The experimental and simulated final water temperatures in the tank are 59.3 °C and 60.9 °C, respectively. Based on these results, an error analysis is carried out. The experimental and simulation results of the system in summer provide a fundamental data and method for predicting the annual performance of the system in the future