How informative is your kinetic model?: using resampling methods for model invalidation
نویسندگان
چکیده
منابع مشابه
Finite Mixture Model Diagnostics Using Resampling Methods
This paper illustrates the implementation of resampling methods in flexmix as well as the application of resampling methods for model diagnostics of fitted finite mixture models. Convenience functions to perform these methods are available in package flexmix. The use of the methods is illustrated with an artificial example and the seizure data set.
متن کاملResampling methods for model fitting and model selection.
Resampling procedures for fitting models and model selection are considered in this article. Nonparametric goodness-of-fit statistics are generally based on the empirical distribution function. The distribution-free property of these statistics does not hold in the multivariate case or when some of the parameters are estimated. Bootstrap methods to estimate the underlying distributions are disc...
متن کاملthe use of appropriate madm model for ranking the vendors of mci equipments using fuzzy approach
abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...
15 صفحه اولComplement: Finite Mixture Model Diagnostics Using Resampling Methods
This paper illustrates the application of resampling methods for model diagnostics of fitted finite mixture models. Convenience functions to perform these methods are available in package flexmix. The results of the application to an artificial example and the seizure data set as described in Grün and Leisch (2010) are reproduced.
متن کاملIs your phylogeny informative? Measuring the power of comparative methods.
Phylogenetic comparative methods may fail to produce meaningful results when either the underlying model is inappropriate or the data contain insufficient information to inform the inference. The ability to measure the statistical power of these methods has become crucial to ensure that data quantity keeps pace with growing model complexity. Through simulations, we show that commonly applied mo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Systems Biology
سال: 2014
ISSN: 1752-0509
DOI: 10.1186/1752-0509-8-61