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, 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.

31 This tells WEKA that we want to build a regression model.

32 This paper discusses the parameter estimation in measuring error secondary polynomial regression model based on Fuller.

33 The third is the ill-condition separation algorithm in multicollinear regression model.

34 This paper presents regression model with same regression coefficient and different regression constants.

35 A SVM based regression model with accurate number input and interval number output.

36 Then, correlation index and regression model are used to forecast population scale, urban quantity and urbanization in Jiangsu province.

37 This paper explores how a proportional hazards regression model may be adapted to the relative survival rates by using software of GLIM.

38 The results showed that the length of score vector in AMMI model was better to explain genotype by environment interaction than by joint linear regression model.

39 By the mean of integration of landslide certainty factor (CF) and multi-variable regression model, some problems can be solved including the selection and quantification of landslide factors.

40 This paper makes use of auto regression model named AR in the array of time to found out the stochastic process of pulse wind. The suitable step number of auto regression ...

41 The sampling distribution and hypothesis testing of this non-linear generalized correlation coefficient will be studied with linear regression model .

42 The use of polynomial regression model with a combination of mutation Qiemo Oasis established mutation model of sustainable development for the future development of the oasis system for reference.

43 In this paper, we discuss the estimate of regression function in nonparametric regression model based on exponential integral martingale difference.

44 A mathematical regression model was presented in this study for the separation of sterols in methyl(esterification) of rapeseed oil deodorized distillate by central composite design.

45 For the linear weighted regression model, this paper defines a new relative efficiency, gives its lower bound and also discusses its relation to other three efficiencies.

46 It's actually quite easy to put our data through the regression model using the WEKA API, far easier than actually loading the data.

47 Nonlinear multiple regression model on the structure activity relationship of ternary dissymmetric organic phosphate insecticide is obtained by quadratic polynomial stepwise regression method.

48 A high precise regression model of rubber formulation was built with the uniform design and GMDH (group method of data handling) method.

49 In this paper, the estimation of the direction of the regression coefficient of general regression model is considered.

50 Descusses the logarithmic correction factors of general multiplicative regression model and percent bias of unadjusted predicted value. The pool of correction factors is proposed.

51 Further, on this basis we derived an instrumental variable regression model. After disregarding the effect of multicollinearity among the explanatory variables, we verify the accuracy of the results.

52 A liner moving mean auto - regression model is developed to forecast the system marginal price.

53 Since the algorithm does not require a prior regression model with unknown variables, it can be utilized in the circumstances where other traditional statistical regression algorithms fail.

54 The effect of deep tube well use on the incidence of childhood diarrhoea was assessed using a random effects negative binomial regression model.

55 There has been four kinds of main early warning models of exchange crisis at present, namely "signal" approach, probit model, cross-county regression model and subjective probability method.

56 Based on the sample data of ship plate, and by applying mathematical statistics and multivariate regression analysis, a regression model of deformation parameter is established.

57 Simple linear regression model is applied to compare the difference in SGA usage pattern between public and private hospitals.

58 This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.

59 Then, a multivariate regression model is developed for measured and calculated results of geostress at measurement points,() and the regression coefficient of the model is derived.

60 After data preprocessing a regression model between calorific and ash content was founded by polynomial regression.

61 Artificial neural network is a kind of implicit expression without explicit expression as statistical regression model, and it is its disadvantage.

62 Examples in this paper show that the dummy variable can draw some quality markers which is impossible to be quantized into the linear regression model.

63 Results The effect of multicollinearity among variables were eliminated in the regression model and an ideal mathematical model was constructed.

64 Objective To research the relationship between the phospholipase activities and the random amplified polymorphic DNA(RAPD) bands of Candida albicans, and establish the regression model.

65 The multiple regression model is the most widely used vehicle for empirical analysis.

66 Then it establishes a stepwise statistical regression model. Finally, the model prediction effect is comparative analysis by comparing the characteristic parameters of the model.

67 The examples indicate that using regression model instead of process and device modelling is superior in process optimized design and device performance prediction.

68 Based on performance features of the mechanical air-flow meter, the regression model for the inspected data is monadic linear model.