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Data mining is a new type of information processing technology. The use of data mining technology in online audit will improve the auditing efficiency and auditing quality, reduce the audit risk, and can provides new powerful weapons for anti-fraud of auditors. Data mining process in online audit includs: auditors putting forward demand, data preparation, data mining and result analysis. The basic...
In order to reveal the relationship between FDI and economic growth in ShaanXi, statistical data of ShaanXi's GDP and FDI from 1994~2009 were used to study the relationship between FDI and economic growth in ShaanXi based on OLS model. The results showed that FDI played a certain role but not the main character in promoting economic growth. Under certain policy the expansion of foreign direct investment...
White-collar workers are high-productivity people arisen in recent years, and they directly affect the economic development situation and development mode in the cities or the areas where they located in, and it is also considered of the change of such population migration. The article will research on the mode and the white-collar population flow in the domestic 30 big/medium cities through the attraction...
The recent studies on financial distress are mostly confined to static econometric or statistical methods based on cross-sectional financial data ,and it is ignored that the variation of companies' financial status is a dynamic process. In order to show the change of companies in financial position, this study constructed the financial distress prediction model based on panel logit. On the selection...
This paper studies discriminant modeling method of compositional data. By adopting logratio transformation of compositional data and then implementing Fisher discriminant modeling method to the transformed data, the logcontrast linear discriminant function of compositional data is derived. The model presents the following advantages: i) the transformed data, which is scaled up to a broader range of...
With the rapid development of database technique and computer technology nowadays, it is no longer a difficult problem to manage mass statistical data with computer and database system. However, from the statistical mode and time series of rural socio-economic statistical survey, we know that the statistical data have both spatial and temporal attribute, so the traditional systems have no enough ability...
Interval-censored data of gaps between recurrent events arise as the exact gaps can not be available but only know, such as whether the event time of interest is no later than the examination time. The recurrent event times subject to this interval censoring are often encountered in epidemiological studies and clinical trials. In this paper we propose a gaps model which is a derivative of the marginal...
In view of the complexity of social impact post-evaluation and relatively inefficient evaluation methods, this paper constructed an index system of social impact post-evaluation of the highway through a combination of inductive and deductive methods based on the analysis of literature surveys and expert surveys and made full use of the superiority of the factor analysis and the advantage of success...
One of the most important simulation applications is the comparison of alternatives. Possible decisions, operating procedures, system designs can be compared through simulation experiments before implementing them in the real life. Stochastic simulation leads to variance of the estimated difference between systems performance measures. The goal of simulation experiments is to obtain point and interval...
A new method for obtaining models of the performance of parallel applications based on statistical analysis is presented in this paper. This method is based on the Akaike's information criterion (AIC) that provides an objective mechanism to rank different models by means of an experimental data fit. The input of the modeling process is a set of variables and parameters that can a priori influence...
The strength of model link lies in analyzing spatial data and generating useful information. The linked model have a quantitative specification essentially like empirically based models: statistical models provide high degrees of precision and specified levels of sensitivity and reliability. It also hoped to solve some problems encountered by empirically based approaches through behavioral parameter...
In this paper, we propose a new diagnostic checking tool for fuzzy rule-based modelling of time series. Through the study of the residuals in the Lagrange multiplier testing framework we devise a hypothesis test which allows us to determine if there is some left autocorrelation in the error series. This is an important step towards a statistically sound modelling strategy for fuzzy rule-based models.
A model of branching structures of apple trees (Malus domestica cv. Fuji) in an intensive orchard for different levels of heading intensities is presented. The model, based on a statistical analysis, essentially simulates the numbers and distributions of the axillary production along one-year-old parent branches using the Hidden Semi-Markov Chain (HSMC), and has been validated against observed data...
Companies in financial distress make the creditors, shareholders, employees, investors and other participants of the related firms suffer great losses. In order to prevent the companies run into bankruptcy, financial distress prediction has been a useful tool for distinguishing companies in financial distress from those healthy. Statistical methods and artificial intelligence techniques have been...
A statistical model has been constructed that extends the phenomenological 99% cumulant model to a full cumulative distribution function for amplitude and phase of the far end crosstalk between twisted pair telephone wires. The offset of the crosstalk amplitude relative to the 99% level is described by a frequency independent beta distribution. Inter-binder crosstalk is modeled by an additional parameter...
The paper takes the customer data in a certain enterprise as the research case, and applies discriminant analysis method of multivariate statistics to customer segmentation in management decision, in order to solve the problem of customer segmentation. The aim of the study is to obtain classification schemes able to support business marketing. The customer classification is implemented by using R...
Statistical models in which both fixed and random effects enter nonlinearly are becoming increasingly popular. These models have a wide variety of applications in many areas such as agriculture, forestry, biology, ecology, biomedicine, sociology, economics, pharmacokinetics, and other areas. Mixed effect models are flexible models to analyze grouped data including longitudinal data, repeated measures...
Knowledge discovery from temporal, spatial and spatiotemporal data is critical for climate change science and climate impacts. Climate statistics is a mature area. However, recent growth in observations and model outputs, combined with the increased availability of geographical data, presents new opportunities for data miners. This paper maps climate requirements to solutions available in temporal,...
A new stochastic stock price model of stock markets based on the contact process of the interacting particle systems is presented in this paper, where the contact model is a continuous time Markov process, one interpretation of this model is as a model for the spread of an infection. Through this model, the statistical properties of Shanghai stock exchange (SSE) composite index are studied. In the...
The accuracy of spatial interpretation is close relation to the selection of spatial model. Each model has its own advantage or disadvantage. A more accurate spatial interpretation model can be obtained by a linear combination of some models. In this study, first-order spatial autoregressive interpretation (SARI(1)) model, kriging algorithm interpretation (KAI) model and back-propagation neural network...
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