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1 A multiple linear regression model was used to assess the independent effects on diabetic control of those variables studied.

2 This correlation is confirmed in the regression model which also shows a negative correlation with education level of project leader.

3 The regression model has a good directional sense to improve furnace, and maintain a sustained and stable production process.

4 Through the use of linear model and nonparametric regression model, the trend of the total foreign exchange reserve account for the proportion of GDP is fitted.

5 In this paper, an inputoutput incremental simple linear regression model is used as a predictive model of black box systems, and a projection algorithm is adopted to estimate the model parameters.

6 This paper builds up a regression model by use of dichotomous variable and estimates the seasonal index indirectly by the parameter estimation of seasonal dichotomous variable.

7 The latent root regression model with near-infrared spectra of 40 soybean samples was founded for analyzing the content of soybean protein in this study.

8 Poisson regression is a regression model for analyzing the dependent variable of count data.

9 Methods Multiple factor logistic regression model were conducted to analyse the field survey data.

10 Objective To sump up and extend COX regression model with categorical variables.

11 The regression model has guiding significance to the study on ternary dissymmetric organic phosphate insecticide.

12 In the Logit regression model, the explaining variables are return on net assets, working capital ratio and per share investment net cash flow. Its predictive power is better than KMV.

13 The piecewise polynomial regression model was established based on analyzing the scatter diagram of the speed change with the install distance.

14 The regression model based on 45 years data (1951-1995) with the two parameters has a multiple correlation coefficient of 0. 66.

15 Through adopting forward selection variables, the relative optimal regression model was achieved.

16 Thirdly, we used a unilinear regression model to verify whether the enterprises listed on SMEs board have an optimal capital structure, and the answer is yes.

17 Shared care did not contribute to the multiple linear regression model.

18 Potential prognostic factors were investigated with Cox's proportional hazards regression model.

19 Time trends and age at diagnosis were evaluated with a linear regression model by the method of least squares.

20 A method to use the grey prediction model and geometric regression model to predict the daily load curve of power systems during the great holiday is proposed. A relevant software is presented.

21 An Empirical Research on the Health Index Forecasting of Zhe Jang Province with Semiparametric Regression Model.

22 This paper developed an alternative approach that can incorporate both traffic count and link attributes through an exponential regression model in estimating volume and VMT.

23 According the characteristics of the flight data, the moving quadric polynomial regression model is established and is transformed to the orthogonal polynomial to calculate the regression coefficient.

24 Combining the methods of regression and time-series analysis, the paper designs a spatiotemporal regression model to predict the population of each province in China.

25 The text analyzes the influencing factors of private forest's cooperative management willingness, through constructing logistic regression model.

26 This paper uses ridge estimation method to solve the potential ill-conditioned problem in semiparametric regression model.

27 In this paper,(www.Sentencedict.com) an evaluation model is set up by utilizing statistical linear regression model method.

28 This paper studies the whole behavior of dent-damaged tubular members with the help of a regression model, which was developed from published test results and finite element analysis.

29 Tea crop area, harvesting area, per unit area yield, gross output, and the total agricultural output value of the tea industry are analyzed and assessed by using regression model analysis.

30 The absorbing forces in rural and urban area use one liner regression model predicting the absorbing power of the secondary industry and the tertiary industry in rural region and the urban as a whole.