Itβs been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Sec
Measurement Error in Nonlinear Models
β Scribed by R. J. Carroll, D. Ruppert, L. A. Stefanski (auth.)
- Publisher
- Springer US
- Year
- 1995
- Tongue
- English
- Leaves
- 327
- Series
- Monographs on Statistics and Applied Probability 63
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Content:
Front Matter....Pages i-xxiv
Introduction....Pages 1-20
Regression and Attenuation....Pages 21-39
Regression Calibration....Pages 40-78
Simulation Extrapolation....Pages 79-106
Instrumental Variables....Pages 107-121
Functional Methods....Pages 122-140
Likelihood and Quasilikelihood....Pages 141-164
Bayesian Methods....Pages 165-181
Semiparametric Methods....Pages 182-198
Unknown Link Functions....Pages 199-205
Hypothesis Testing....Pages 206-214
Density Estimation and Nonparametric Regression....Pages 215-228
Response Variable Error....Pages 229-242
Other Topics....Pages 243-256
Back Matter....Pages 257-305
π SIMILAR VOLUMES
Itβs been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Sec
ItΠ²Πβ’s been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, <b>Measurement Error in Nonlinear Models: A Modern Perspecti
<p>It`s been over a decade since the first edition of <i>Measurement Error in Nonlinear Models</i> splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, <b>Measurement Error in Nonlinear Models: A Modern Per