James Durbin
(Deceased since 20120623)
Names
first:  James 
last:  Durbin 
Contact
homepage:  http://en.wikipedia.org/wiki/James_Durbin 
Research profile
author of:

Time Series Analysis by State Space Methods
by Durbin, James & Koopman, Siem Jan 
Filtering and smoothing of state vector for diffuse state‐space models
by S. J. Koopman & J. Durbin 
Maximum Likelihood Estimation of the Parameters of a System of Simultaneous Regression Equations
by Durbin, James 
Approximations for densities of sufficient estimators
by Durbin, J. 
Estimation of Regression Coefficients of Interest When Other Regression Coefficients Are of No Interest
by Jan R. Magnus & J. Durbin 
Testing for Serial Correlation in LeastSquares Regression When Some of the Regressors are Lagged Dependent Variables.
by Durbin, J. 
A simple and efficient simulation smoother for state space time series analysis
by J. Durbin 
Is a philosophical consensus for statistics attainable?
by Durbin, J. 
Reply to Stephen E. Fienberg's discussion
by Durbin, J. 
An efficient and simple simulation smoother for state space time series analysis
by J. Durbin and S. J. Koopman 
Seasonal Adjustment When the Seasonal Component Behaves Neither Purely Multiplicatively nor Purely Additively
by J. Durbin & P. B. Kenny
edited by 
Time Series Analysis by State Space Methods
by Durbin, James & Koopman, Siem Jan 
Time series analysis of non‐Gaussian observations based on state space models from both classical and Bayesian perspectives
by J. Durbin & S. J. Koopman 
An Alternative to the Bounds Test for Testing for Serial Correlation in LeastSquares Regression.
by Durbin, J. 
A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance
by Magnus, J. R. & Durbin, J. 
Fast Filtering and Smoothing for Multivariate State Space Models
by Koopman, S. J. M. & Durbin, J. 
Time Series Analysis of NonGaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives
by Durbin, J. & Koopman, S. J. M. 
Fast Filtering and Smoothing for Multivariate State Space Models
by S. J. Koopman & J. Durbin 
Benchmarking by State Space Models
by J. Durbin & B. Quenneville 
Design of Multi‐Stage Surveys for the Estimation of Sampling Errors
by J. Durbin 
Appendix: Statistical Requirements of the AIDS Epidemic
by John Kingman & J. Durbin & David Cox & M. J. R. Healy 
Fast Filtering and Smoothing for Multivariate State Space Models
by Koopman, S. J. M. & Durbin, J. 
A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance
by Magnus, J. R. & Durbin, J. 
Time Series Analysis of NonGaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives
by Durbin, J. & Koopman, S. J. M.