Introduction to Nonlinear Regression
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چکیده
منابع مشابه
Comparison of time to the event and nonlinear regression models in the analysis of germination data
Extended abstract Introduction: Numerous studies are being carried out to reveal the effects of different treatments on the germination of seeds from various plants. The most commonly used method of analysis is the nonlinear regression which estimates germination parameters. Although the nonlinear regression has been performed based on different models, some serious problems in its structure...
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Extended abstract Introduction: Germination speed is one of the most important germination indices, which is used in the most studies to compare the effects of different treatments on germination of seeds. Researchers use the reverse time to 50% maximum germination (1/D50) to calculate the germination rate. One of the methods for calculating the D50 is the use of nonlinear regression models s...
متن کاملModeling of monthly flow duration curve using nonlinear regression method for un-gauged watersheds of Ardabil Province
The flow duration curve (FDC) represents the frequency distribution of water flow over a period of time, which is widely used in hydrology to evaluate different ranges of river water flow applications. Therefore, it is necessary to develop a suitable estimation model and method in un-gauged watersheds. To this end, in the present study, a modeling method based on nonlinear regression, for the p...
متن کاملTests Based on Regression Rank Scores in Nonlinear Models and Their Computation
We consider a nonlinear regression model introduced in Jurečková [2006], where concept of regression rank scores was generalized to nonlinear models. We try to support by simulations the results (asymptotic properties under some regularity conditions) proven in that article and apply them to a set of real data. We test a two sample problem under nuisance nonlinear regression pointing out some d...
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This lab is about two topics in modeling. Interaction refers to a particular way of structuring models; it is a concept that applies to a wide variety of models. Logistic Regression is a form of nonlinear modeling that is particularly useful when the response variable is binomial, e.g., yes or no, alive or dead, success or failure. The two concepts are brought together in this lab only because ...
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