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In: Contributions to Statistics
In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models
In: Quantitative applications in the social sciences 20
In: Use R!; Political Analysis Using R, S. 99-125
In: Sage University papers
In: Quantitative applications in the social sciences 97
In: Sage university papers
In: Quantitative applications in the social sciences 145
Providing a thorough introduction to generalized linear models (GLM), exponential family distribution & maximum likelihood estimation, this book includes discussion on checking model adequacy & description on how to use a popular statistical software programme, SAS, to fit GLM
In: Statistica Neerlandica, Band 34, Heft 2, S. 125-125
ISSN: 1467-9574
In: Quantitative applications in the social sciences 170
In: Prentice-Hall series in educational measurement, research, and statistics
SSRN
In: Management Science, S. 367-418
In: Social science research: a quarterly journal of social science methodology and quantitative research, Band 53, S. 118-136
ISSN: 1096-0317