Curve Fitting & Nonlinear Regression (Statistical Associates Blue Book Series 25) (English Edition) [Kindle-editie] beoordelingen het boek quotes

CURVE FITTING & NONLINEAR REGRESSIONOverviewBoth curve fitting and nonlinear regression are methods of finding a best-fit line to a set of data points even when the best-fit line is nonlinear.Below, curve-fitting is discussed with respect to the SPSS curve estimation module, obtained by selecting Analyze > Regression > Curve Estimation. This module can compare linear, logarithmic, inverse, quadratic, cubic, power, compound, S-curve, logistic, growth, and exponential models based on their relative goodness of fit where a single dependent variable is predicted by a single independent variable or by a time variable. As such it is a useful exploratory tool preliminary to selecting multivariate models in generalized linear modeling, which supports nonlinear link functions. (Generalized linear modeling is treated in a separate Statistical Associates "Blue Book" volume).The province of nonlinear regression is fitting curves to data which cannot be fitted using nonlinear transforms of the independent variables or by nonlinear link functions which transform the dependent variable. This type of data is "intrinsically nonlinear" and requires approaches treated in a second section of this e-book, which covers nonlinear regression in SPSS, obtained by selecting Analyze > Regression > Nonlinear. Coverage: SPSS.The full content is now available from Statistical Associates Publishers. http://www.statisticalassociates.com.Below is the unformatted table of contents.CURVE FITTING AND NONLINEAR REGRESSIONTable of ContentsOverview 5Curve Fitting 5Key Concepts and Terms 5Curve Estimation dialog in SPSS 5Models 6Statistical output for the SPSS curve estimation module 19Comparative fit plots 19Regression coefficients 20R-square 21Analysis of variance table 21Saved variables 23Curve Estimation Assumptions 23Data dimensions 23Data level 24Randomly distributed residuals 24Independence 24Normality 24Curve Fitting: Frequently Asked Questions 24Can the SPSS Curve Estimation module tell me what type of model I need (ex., linear, logarithmic, exponential)? 24I want to use, from the Curve Estimation module, the two best functions of my independent in a regression equation, but will this introduce multicollinearity? 30What software other than SPSS is available for curve fitting? 30Nonlinear Regression 32Overview 32Key Concepts and Terms 33Linearization 33Nonlinear regression example 36Entering a model 36Parameters 37Other input options 38Statistical Output 41Parameter Estimates Table 42Correlation of Parameter Estimates Table 43ANOVA Table and R2 44Modeling multiple individuals 44Overview 44Data setup 44Segmented models 46Conditional logic statements 46Alternative models as multiple conditions 46Nonlinear regression assumptions 47Data level 47Proper specification 47Nonlinear regression: Frequently asked questions 48Bibliography 51Pagecount: 53