This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics.
For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method.
Treats linear regression diagnostics as a tool for application of linear regression models to real-life data.
Monthly Weather Review 130, 629–648. l'Ecuyer, P. and T. Andres (1997). A random number generator based on the combination of four LCGs. Mathematics and Computers in Simulation 44, 99–107. Li, G., J. Hu, S.-W. Wang, P. Georgopoulos, ...
In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.
This book provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties.
This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols.
Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or ...
He assumed that (1) over the ensemble of networks, the weights of a particular layer all have the same variance, (2) the weights in the networks are statistically independent and (3) the mean value of each weight of the network over the ...
In this 2-volume set, first- and second- order design sensitivity analyses are presented for static and dynamics responses of both linear and nonlinear elastic structural systems, including elasto-plastic and frictional contact problems.
In practicc, dccision makers often provide only partial and/or doubtful information. We unify and expand results to deal with those cases introducing a general framework for sensitivity analysis in multi-objective decision making.