Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

Depressed Older Patients’ Need for and Expectations of Improved Health Services—An Evaluative Approach to the Chronic Care Model

Depression in later life is an underrepresented yet important research area. The aim of the study was to explore depressed older persons’ need for and expectations of improved health services one year after implementation of the Chronic Care Model (CCM). A qualitative evaluative design was used. Data were collected through individual interviews with older persons living in Norway. The qualitative content analysis revealed two themes: The need to be safeguarded and Expectation of being considered valuable and capable. Evaluation of the improvement in care with focus on the CCM components showed that the most important components for improving the depressed older person’s daily life were: delivery system re-design, self-management support, productive interaction and a well-informed active patient. The findings highlight the need for a health services designed for persons suffering from chronic ill-health, where the CCM could serve as a framework for policy change and support the redesign of the existing healthcare system. We conclude that older persons with depression need attention, especially those who have been suffering for many years. The identified components may have implications for health professionals in the promotion of mental healthcare.

Integration of Expectation Maximization using Gaussian Mixture Models and Naïve Bayes for Intrusion Detection

Intrusion detection is the investigation process of information about the system activities or its data to detect any malicious behavior or unauthorized activity.Most of the IDS implement K-means clustering technique due to its linear complexity and fast computing ability.Nonetheless,it is Naïve use of the mean data value for the cluster core that presents a major drawback.The chances of two circular clusters having different radius and centering at the same mean will occur.This condition cannot be addressed by the K-means algorithm because the mean value of the various clusters is very similar together.However,if the clusters are not spherical,it fails.To overcome this issue,a new integrated hybrid model by integrating expectation maximizing(EM)clustering using a Gaussian mixture model(GMM)and naïve Bays classifier have been proposed.In this model,GMM give more flexibility than K-Means in terms of cluster covariance.Also,they use probabilities function and soft clustering,that’s why they can have multiple cluster for a single data.In GMM,we can define the cluster form in GMM by two parameters:the mean and the standard deviation.This means that by using these two parameters,the cluster can take any kind of elliptical shape.EM-GMM will be used to cluster data based on data activity into the corresponding category.

The Expected Discounted Tax Payments on Dual Risk Model under a Dividend Threshold

In this paper, we consider the dual risk model in which periodic taxation are paid according to a loss-carry-forward system and dividends are paid under a threshold strategy. We give an analytical approach to derive the expression of gδ(u) (i.e. the Laplace transform of the first upper exit time). We discuss the expected discounted tax payments for this model and obtain its corresponding integro-differential equations. Finally, for Erlang (2) inter-innovation distribution, closedform expressions for the expected discounted tax payments are given.

Cybersecurity: A Statistical Predictive Model for the Expected Path Length

The object of this study is to propose a statistical model for predicting the Expected Path Length (expected number of steps the attacker will take, starting from the initial state to compromise the security goal—EPL) in a cyber-attack. The model we developed is based on utilizing vulnerability information along with having host centric attack graph. Utilizing the developed model, one can identify the interaction among the vulnerabilities and individual variables (risk factors) that drive the Expected Path Length. Gaining a better understanding of the relationship between vulnerabilities and their interactions can provide security administrators a better view and an understanding of their security status. In addition, we have also ranked the attributable variables and their contribution in estimating the subject length. Thus, one can utilize the ranking process to take precautions and actions to minimize Expected Path Length.

A Study on consumers＇ continuing to use online group-buying platforms： The impact of price performance expectations

In this study, we aim to understand the characteristics of online group-buying consumers and to investigate salient factors which influence the continuance intention of online group-buying platforms （OGBP） to bridge this knowledge gap. An expectation-confirmation model of information systems （IS） continuance is adapted to construct a research model in online group-buying contexts. A total of 289 complete and valid responses were collected. Our findings contribute to academics and practitioners in two ways： Firstly, our respondents show that they are young （93% of the respondents＇ ages range between 19 and 28 years old）, female （88% of the respondents）, and thrifty （82% of the respondents＇ transaction amounts are below US$16）. Secondly, based on our results, price performance expectations have a direct impact on confirmation. In addition, in contrast to the IS continuance model （Bhattacherjee, 2001）, the effect of perceived usefulness on satisfaction is not supported. Thus, in online group-buying settings, confirmation is the key antecedent of satisfaction. Satisfaction and perceived usefulness are significantly associated with OGBP continuance intention. Consequently, in addition to offering a wide assortment of merchandise and a convenient online shopping experience to enhance customers＇ perceived usefulness of OGBP, OGBP managers should aim low-price marketing strategies at this female, young, thrifty and price-sensitive segment to transcend consumers＇ price expectations and attract consumers＇ continued intention to visit OGBP.

On the Expected Present Value of Total Dividends in a Risk Model with Potentially Delayed Claims

In this paper, we consider a risk model in which two types of individual claims, main claims and by-claims, are defined. Every by-claim is induced by the main claim randomly and may be delayed for one time period with a certain probability. The dividend policy that certain amount of dividends will be paid as long as the surplus is greater than a constant dividend barrier is also introduced into this delayed claims risk model. By means of the probability generating functions, formulae for the expected present value of total dividend payments prior to ruin are obtained for discrete-type individual claims. Explicit expressions for the corresponding results are derived for K n claim amount distributions. Numerical illustrations are also given.

Reduced Life Expectancy Model Analyses of Exposure Time Effects of Endocrine Disruptors to Teleost Fishes Based on Effect Concentration of Hepatic Biomarkers

In this current paper, the exposure time effects on four endocrine disruptors and teleost fishes were evaluated using the reduced life expectancy (RLE) model based on the effect concentration (EC50) of available literature published. The result on the regression analysis over different exposure times has demonstrated that the EC50 of hepatic biomarkers falls with increasing exposure times in a predictable manner. The slopes of the regression equations reflect the strength of the toxic effects on the various teleost fish. The EC50 reduction over time can be interpreted based on the bioconcentration process, which can be used to understand transfer routes of the compounds from water to fish body. RLE model also provides useful information in assessing the toxic effects on fish life expectancy as a result of the occurrence of compounds.

Test of Ordered Multivariate Discrete Selection Model for Average Life Expectancy

At present, there are significant regional differences in average life expectancy among countries in the world. Not only is there a great disparity in average life expectancy, but also the gender difference is positive and negative, and is distributed in a bipolar distribution of “long life in rich countries and short life in poor countries”. This paper analyzes the factors affecting the life grade by using the ordered multivariate discrete selection model and combined with the average life expectancy data of countries all over the world in 2017. The test results show that: 1) The growth of per capita GDP, elderly dependency ratio and the proportion of people using at least basic drinking water services can effectively improve the level of life expectancy;2) The birth rate has an inhibitory effect on the average life expectancy;3) Through model comparison, probit model is more suitable for the analysis of this kind of problems than logit model, and the properties of the obtained model are better.

Impact of cancer diagnosis on life expectancy by area-level socioeconomic groups in New South Wales, Australia: a population-based study

Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common cancers.Results: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average LOLE.Conclusions: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expectancy.

Research on the Construction and Application of Service Quality Evaluation Models for Scenic Spots:Taking Chongqing Ciqikou as an Example

In the current environment of increasingly fierce competition in the tourism industry,service quality has become crucial for enhancing the competitiveness of scenic spots.This paper uses the SERVQUAL model to design a service quality evaluation questionnaire that captures the gap between tourists’expectations and perceptions,using the Ciqikou Scenic Spot as a case study.Data collected from field surveys are used to comprehensively and meticulously evaluate the service quality of the Ciqikou Scenic Spot.The analysis results show that the scenic spot,with its unique folk culture experience and beautiful ecological environment,has certain advantages in terms of service quality.However,significant deficiencies exist in infrastructure and environmental hygiene.Accordingly,targeted improvement suggestions are proposed to further enhance the service quality of the Ciqikou Scenic Spot and meet the increasingly diverse and personalized needs of tourists.This study provides not only a specific service quality improvement strategy for the Ciqikou Scenic Spot but also a valuable reference for other tourist attractions.

Modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

EFFECTIVE IMAGE SEGMENTATION FRAMEWORK FOR GAUSSIAN MIXTURE MODEL INCORPORATING LOCAL INFORMATION

A new two-step framework is proposed for image segmentation. In the first step, the gray-value distribution of the given image is reshaped to have larger inter-class variance and less intra-class variance. In the sec- ond step, the discriminant-based methods or clustering-based methods are performed on the reformed distribution. It is focused on the typical clustering methods-Gaussian mixture model （GMM） and its variant to demonstrate the feasibility of the framework. Due to the independence of the first step in its second step, it can be integrated into the pixel-based and the histogram-based methods to improve their segmentation quality. The experiments on artificial and real images show that the framework can achieve effective and robust segmentation results.

基于KANO模型的护患双方对专科护理门诊关怀行为期望比较

目的探究专科护理门诊护患双方对关怀行为的期望,为高效实施护理人文关怀提供依据。方法以华生关怀理论为框架,基于关怀评价量表,结合文献回顾、半结构化访谈、德尔菲专家函询,形成专科护理门诊患者22项关怀行为需求指标。应用KANO模型设计调查问卷,采用便利抽样法于2023年5-6月,对河南省5所三级甲等医院1309例在专科护理门诊就诊的患者和119名专科护理门诊护士进行调查。结果22项关怀行为中,患者视角下归于必备属性5项、期望属性6项、魅力属性11项,其中满意系数Better值最高的为“多种途径的预约挂号”,不满意系数Worse值最高的是“治疗护理中保护您的个人隐私”;基于Better-Worse指数的分类显示,必备属性9项、期望属性2项、魅力属性11项。护患双方对21项关怀行为的KANO属性构成分布比较,差异有统计学意义(均P<0.05),KANO属性构成分布一致的项目仅1项。结论专科护理门诊服务应在满足必备属性的基础上,着力提高期望属性,并尽力满足魅力属性。护患双方在关怀行为属性构成上存在较大偏差,护士应加强患者需求为导向的人文关怀服务,以满足患者需求,提高满意度。

Clustering in the Wireless Channel with a Power Weighted Statistical Mixture Model in Indoor Scenario

Cluster-based channel model is the main stream of fifth generation mobile communications, thus the accuracy of clustering algorithm is important. Traditional Gaussian mixture model (GMM) does not consider the power information which is important for the channel multipath clustering. In this paper, a normalized power weighted GMM (PGMM) is introduced to model the channel multipath components (MPCs). With MPC power as a weighted factor, the PGMM can fit the MPCs in accordance with the cluster-based channel models. Firstly, expectation maximization (EM) algorithm is employed to optimize the PGMM parameters. Then, to further increase the searching ability of EM and choose the optimal number of components without resort to cross-validation, the variational Bayesian (VB) inference is employed. Finally, 28 GHz indoor channel measurement data is used to demonstrate the effectiveness of the PGMM clustering algorithm.

The Survival Probability in Generalized Poisson Risk Model

In this paper we generalize the aggregated premium income process from a constant rate process to a poisson process for the classical compound Poinsson risk model,then for the generalized model and the classical compound poisson risk model ,we respectively get its survival probability in finite time period in case of exponential claim amounts.

A multi-target tracking algorithm based on Gaussian mixture model

Since the joint probabilistic data association(JPDA)algorithm results in calculation explosion with the increasing number of targets,a multi-target tracking algorithm based on Gaussian mixture model(GMM)clustering is proposed.The algorithm is used to cluster the measurements,and the association matrix between measurements and tracks is constructed by the posterior probability.Compared with the traditional data association algorithm,this algorithm has better tracking performance and less computational complexity.Simulation results demonstrate the effectiveness of the proposed algorithm.

On two actuarial quantities for the compound Poisson risk model with tax and a threshold dividend strategy

In this paper, we consider a compound Poisson risk model with taxes paid according to a loss-carry-forward system and dividends paid under a threshold strategy. First, the closed-form expression of the probability function for the total number of taxation periods over the lifetime of the surplus process is derived. Second, analytical expression of the expected accumulated discounted dividends paid between two consecutive taxation periods is provided. In addition, explicit expressions are also given for the exponential individual claims.

Does the EVA valuation model explain the market value of equity better under changing required return than constant required return?

Through the Economic-Value-Added(EVA)valuation model,the expected market value of equity can be determined by adding the book value of equity with the present value of expected EVAs under the assumption of constant required return and constant return on equity.The equation of EVA valuation model has taken its shape under the assumption of constant required return and constant return on equity.However,a large body of empirical evidence indicates that required rate of return never remain constant.The EVA-valuation model formulated under constant required return cannot be implemented under the scenario of changing required return.In this study,we explored whether the EVA valuation model could be implemented under changing required return by making any changes in the model and found that it could be implemented under the scenario of changing required return by replacing the book value of the equity of the existing model with the present value of required earnings or normal market earnings.We further examined whether the explanatory ability of the EVA valuation model under the assumption of changing required return is better than that of the valuation model under the assumption of constant required return.Relative information content analyses were conducted by considering sample of the intrinsic value of equities determined by valuation models and the market value of equities of 69 large-cap,88 mid-cap,and 79 small-cap companies.The results showed that the EVA-based valuation model with changing normal market return outperformed the EVA-based valuation model with constant required return.