Peanut consumption and reduced risk of colorectal cancer in women:A prospective study in Taiwan

瞄准：检验花生消费是否与肤色的减少的风险被联系在有 10 年的后续的一个未来的队的表面的癌症。方法：在 1990-1992，在 7 个镇区的居民(30 ～ 65 年的 12026 个男人和 11917 个女人) ，台湾，被会见并且招募并且每年列在后面起来进一个屏蔽癌症的队。在这个队的 Colorectal 癌症诉讼从癌症登记和死亡证被识别。在 2001 底的这疾病的发生率被性为主要学习变量和 covariates 计算。饮食的吸入借助于每周的食物频率措施被估计，包括包括甘薯，豆子产品，花生产品， pickled 食品， nitrated 或吸的食品的经常消费的食物组和民间盘子。结果：在学习经期期间， 107 新肤色表面的癌症盒子(68 个男人和 39 个女人) 被证实。多，变量考克斯的比例的危险模型证明花生消费的相对风险(RR ) 是 0.73 [95% 信心间隔(CI )= 0.44-1.21 ] 为男人并且 0.42 (95% CI = 0.21-0.84 ) 为女人。然而， pickled 食品的经常的吸入为女人是有害的(RR = 2.15， 95% CI = 0.99-4.65 ) 。表面的癌症也是的颜色的风险在香烟吸烟者之中提高了然而并非重要(P【0.05 ) 。结论：这研究建议花生和它的产品的经常的吸入可以减少表面的癌症在女人冒的风险的颜色，表明花生吸入的增殖反的效果。

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models:An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.

Profile Evolution and Energy Dissipation for Internal SolitonTransmitting over Different Submarine Ridges

Fundamental experiments were carried out in a wave flume on internal solitary wave （ISW） of depression-type propagating over a submerged ridge. The seabed ridge included either triangular or semicircular shape - regarded as topographic obstacles. Influenced by the submarine ridge, the transmitted waves were found to always consist of a leading pulse （a solitary wave） followed by a dispersive wave train. The wave profile propagating over a triangular ridge was similar to that caused by a semicircular obstacle. Apparently, the smooth face of a semicircular ridge produced time lag of wave propagation. From experimental results available, the reduction in wave energy induced by a semicircular ridge was larger than that by a triangular one. The events of wave distortion, strong breaking, internal bolus, and stratification mixing happened in case that the crest of an ISW was great enough to interact with the topographic obstacle. The reduction in wave energy was induced by strong breaking, and it depended on the ridge height rather than the geometric shape of the ridge.

Accuracy Evaluation of A Diagnostic Test by Detecting Outliers and Influential Observations

Logit regression analysis is widely applied in scientific studies and laboratory experiments, where skewed observations on a data set are often encountered. A number of problems with this method, for example, oudiers and influential observations, can cause overdispersion when a model is fitted. In this study a systematic statistical approach, including the plotting of several indices is used to diagnose the lack-of-fit of a logistic regression model. The outliers and influential observations on data from laboratory experiments are then detected. Specifically we take account of the interaction of an internal sohtary wave （ISW） with an obstacle, i.e., an underwater ridge, and also analyze the effects of the ridge height, the lower layer water depth, and the potential energy on the amplitude-based transmission rate of the ISW. As concluded, the goodness-of-fit of the revised logit regression model is better than that of the model without this approach.

Computation Analysis of Brand Experience Dimensions: Indian Online Food Delivery Platforms

Online Food Delivery Platforms(OFDPs)has witnessed phenomenal growth in the past few years,especially this year due to the COVID-19 pandemic.This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers.The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience(BEX)dimension that helps in enhancing the brand equity(BE)of OFDPs.BEXs are critical for building brand loyalty(BL)and making companies profitable.Customers can experience different kinds of brand experiences through feeling,emotions,affection,behavior,and intellect.The present research work is taken up to analyze the factors affecting BEX and its impact on BL and BE of the OFDPs and analyze the mediating role of BL in the relationship between BEX and BE of the OFDPs in the Indian context.A survey of 457 Indian customers was carried out.A questionnaire was used for data collection and a mediation study was used to test hypothesized relationships.Our computational analysis reveals that BEX influences the BL and BE of OFDPs.The study further indicates that BL mediates the relationship between BEX and BE of OFDPs.The effective marketing and relationship management practices will help company to enhance BEX that will enable in enhancing BL and raising BE of their product.It therefore provides a more thorough analysis of BEX constructs and their consequences than previous research.Some of the managerial implication,limitations,and scope of future research are also presented in the study.

Wavelet Based Detection of Outliers in Volatility Time Series Models

We introduce a new wavelet based procedure for detecting outliers in financial discrete time series.The procedure focuses on the analysis of residuals obtained from a model fit,and applied to the Generalized Autoregressive Conditional Heteroskedasticity(GARCH)like model,but not limited to these models.We apply the Maximal-Overlap Discrete Wavelet Transform(MODWT)to the residuals and compare their wavelet coefficients against quantile thresholds to detect outliers.Our methodology has several advantages over existing methods that make use of the standard Discrete Wavelet Transform(DWT).The series sample size does not need to be a power of 2 and the transform can explore any wavelet filter and be run up to the desired level.Simulated wavelet quantiles from a Normal and Student t-distribution are used as threshold for the maximum of the absolute value of wavelet coefficients.The performance of the procedure is illustrated and applied to two real series:the closed price of the Saudi Stock market and the S&P 500 index respectively.The efficiency of the proposed method is demonstrated and can be considered as a distinct important addition to the existing methods.

Forecasting Stock Volatility Using Wavelet-based Exponential Generalized Autoregressive Conditional Heteroscedasticity Methods

In this study,we proposed a new model to improve the accuracy of fore-casting the stock market volatility pattern.The hypothesized model was validated empirically using a data set collected from the Saudi Arabia stock Exchange(Tada-wul).The data is the daily closed price index data from August 2011 to December 2019 with 2027 observations.The proposed forecasting model combines the best maximum overlapping discrete wavelet transform(MODWT)function(Bl14)and exponential generalized autoregressive conditional heteroscedasticity(EGARCH)model.The results show the model's ability to analyze stock market data,highlight important events that contain the most volatile data,and improve forecast accuracy.The results were compared from a number of mathematical mod-els,which are the non-linear spectral model,autoregressive integrated moving aver-age(ARIMA)model and EGARCH model.The performance of the forecasting model will be evaluated based on some of error functions such as Mean absolute percentage error(MAPE),Mean absolute scaled error(MASE)and Root means squared error(RMSE).

Effects of Location Diversification and Corporate Governance on Multinational Enterprises＇ Financial Performance and Risk-taking： Evidence from Taiwan Residents Enterprises

This study investigates the location choice performance of foreign direct investment （FD1） originating from small- and medium-sized multinational enterprises established in newly industrialized economies. In this study we integrate location diversification, breadth and corporate governance to examine the performance of Taiwan Residents enterprises investing in Chinese mainland. Examining Taiwan Residents manufacturing enterprises from foundational, traditional and high-technology aspects, our findings demonstrate the following： （i） diversifying the location choice negatively affects the return of assets; （ii） investments in regions with an abundant population positively affect the performance of Taiwan Residents traditional manufacturing enterprises; and （iii） a higher percentage of insider hoMings in Taiwan Residents enterprises results in better FDl performance. We conclude that the performance of FDI originating from Taiwan Residents enterprises varies depending on industrial and governance characteristics. We suggest that the location choice for Taiwan FDI in Chinese mainland should be determined by the characteristics of the industry. Chinese mainland should attract multinational enterprises from emerging markets according to the characteristics of regions.

Estimating Loss Given Default Based on Beta Regression

Loss given default(LGD)is a key parameter in credit risk management to calculate the required regulatory minimum capital.The internal ratings-based(IRB)approach under the Basel II allows institutions to determine the loss given default(LGD)on their own.In this study,we have estimated LGD for a credit portfolio data by using beta regression with precision parameter(∅)and mean parameter(μ).The credit portfolio data was obtained from a banking institution in Jordan;for the period of January 2010 untilDecember 2014.In the first stage,we have used the“outstandingamount”and“amount of borrowing”to find LGD of each default borrower(494 out of 4393 borrower).In the second stage,we fit univariate parametric distributions to the LGD data to obtain the beta distribution.After that,we have estimated the values of∅based on microeconomic variables(SPP,OE and LR).Moreover,we have estimated the values ofμbased on macroeconomic variables(GDP and Inflation rate).Finally,we have compared between six different link functions(Logit,loglog,probit,cloglog,cauchit,and log),which have used with∅andμ.The results show that Beta regression with probit link function has the highest R-squared with accepted measurements for logL,AIC and BIC.

Fuzzy cost-profit tradeoff model for locating a vehicle inspection station considering regional constraints

Facility location allocation(FLA) is one of the important issues in the logistics and transportation fields. In practice, since customer demands, allocations, and even locations of customers and facilities are usually changing, the FLA problem features uncertainty. To account for this uncertainty, some researchers have addressed the fuzzy profit and cost issues of FLA. However, a decision-maker needs to reach a specific profit, minimizing the cost to target customers. To handle this issue it is essential to propose an effective fuzzy cost-profit tradeoff approach of FLA. Moreover, some regional constraints can greatly influence FLA. By taking a vehicle inspection station as a typical automotive service enterprise example, and combined with the credibility measure of fuzzy set theory, this work presents new fuzzy cost-profit tradeoff FLA models with regional constraints. A hybrid algorithm integrating fuzzy simulation and genetic algorithms(GA) is proposed to solve the proposed models. Some numerical examples are given to illustrate the proposed models and the effectiveness of the proposed algorithm.

Innovation： An Eternal Theme in the Development of Pediatrics

The health problems of children differ greatly from those of adults. A child＇s response to illness and stress varies with increasing age. Pediatrics is a discipline that examines all aspects of the well-being of fetuses, infants, children, and adolescents, including their physical, mental, and psychologic growth and development. The development of pediatrics relies on innovation. Innovation is defined as the combination of new ideas, including new concepts, science, technology, and theories, which advance the development of various disciplines of pediatrics. Innovation has a strong influence on pediatrics, especially in promoting the quality of life of children, preventing diseases, and protecting children from health threats. Indeed, innovation is a driving force of the development of pediatric studies, providing the latest knowledge, theories, and technologies in pediatrics.

Empirical likelihood test for the equality of several high-dimensional covariance mat rices

The testing covariance equality is of importance in many areas of statistical analysis,such as microarray analysis and quality control.Conventional tests for the finite-dimensional covariance do not apply to high-dimensional data in general,and tests for the high-dimensional covariance in the literature usually depend on some special structure of the matrix and whether the dimension diverges.In this paper,we propose a jackknife empirical likelihood method to test the equality of covariance matrices.The asymptotic distribution of the new test is regardless of the divergent or fixed dimension.Simulation studies show that the new test has a very stable size with respect to the dimension and it is also more powerful than the test proposed by Schott(2007)and studied by Srivastava and Yanagihara(2010).Furthermore,we illustrate the method using a breast cancer dataset.

Jackknife empirical likelihood test for the equality of degrees of freedom in t-copulas

It has been argued that fitting a t-copula to financial data is superior to a normal copula. To overcome the shortcoming that a t-copula only has one parameter for the degrees of freedom, the t-copula with multiple parameters of degrees of freedom has been proposed in the literature, which generalizes both the t-copulas and the grouped t-copulas. Like the inference for a t-copula, a computationally efficient inference procedure is to first estimate the correlation matrix via Kendall's τ and then to estimate the parameters of degrees of freedom via pseudo maximum likelihood estimation. This paper proposes a jackknife empirical likelihood test for testing the equality of some parameters of degrees of freedom based on this two-step inference procedure, and shows that the Wilks theorem holds.

Precautionary Effort Investment under Cross Risk Aversion

This paper deals with the effort problem under multiple risks in bivariate utility setting. We identify preference conditions to insure positive or negative effect of a background variable uncertainty on effort in the presence of other risks. We allow for the simultaneous presence of wealth and background variable uncertainties. We investigate the joint effect of two-source uncertainties on effort when two risks are either small or positive quadrant dependent. Our work extends the previous model of effort to bivariate utility framework and presents new insights into the issue of optimal effort under uncertainty.

Priority Setting in Health Care with Disease and Treatment Risks

This paper deals with the issue of priority setting in health care under uncertainties about the severity of the illness and the effectiveness of medical treatment. We examine the effect of a disease uncertainty(a treatment uncertainty) on the allocation of health care resources in the presence of a treatment risk(a disease risk) and identify preference conditions under which the social planner allocates more resources to higher risk population. We allow for the simultaneous presence of two risks and investigate the joint effect of two-source uncertainties on health care allocation when the two risks are either small or positively quadrant dependent. The effect of inequality aversion on health care allocation is also analyzed by introducing an equity weighting function. Our work extends the previous model of health care priority to two-risk framework and provides new insights into the problem of health care decision making under uncertainty.

Dynamic bivariate normal copula

Normal copula with a correlation coefficient between-1 and 1 is tail independent and so it severely underestimates extreme probabilities. By letting the correlation coefficient in a normal copula depend on the sample size, H¨usler and Reiss(1989) showed that the tail can become asymptotically dependent. We extend this result by deriving the limit of the normalized maximum of n independent observations, where the i-th observation follows from a normal copula with its correlation coefficient being either a parametric or a nonparametric function of i/n. Furthermore, both parametric and nonparametric inference for this unknown function are studied, which can be employed to test the condition by H¨usler and Reiss(1989). A simulation study and real data analysis are presented too.

Random difference equations with subexponential innovations

We consider the random difference equations S =_d(X + S)Y and T =_dX + TY, where =_ddenotes equality in distribution, X and Y are two nonnegative random variables, and S and T on the right hand side are independent of(X, Y). Under the assumptions that X follows a subexponential distribution with a nonzero lower Karamata index, that Y takes values in [0, 1] and is not degenerate at 0 or 1, and that(X, Y) fulfills a certain dependence structure via the conditional tail probability of X given Y, we derive some asymptotic formulas for the tail probabilities of the weak solutions S and T to these equations. In doing so we also obtain some by products which are interesting in their own right.