Estimate one-step ahead expectation and variance of \(y_{t}\) conditional on observed time series until the instant \(t-1\).
pgam.fit(w, y, eta, partial.resid)
vector of one-step ahead prediction
vector partial residuals
estimate of discount factor \(\omega\) of a Poisson-Gamma model
observed time series which is the response variable of the model
semiparametric predictor
type of partial residuals.
Washington Leite Junger wjunger@ims.uerj.br and Antonio Ponce de Leon ponce@ims.uerj.br
Partial residuals for semiparametric estimation is extracted. Those are regarded to the parametric partition fit of the model. Available types are raw, pearson and deviance. The type raw is prefered. Properties of other form of residuals not fully tested. Must be careful on choosing it.
See details in predict.pgam and residuals.pgam.
Harvey, A. C., Fernandes, C. (1989) Time series models for count data or qualitative observations. Journal of Business and Economic Statistics, 7(4):407--417
Harvey, A. C. (1990) Forecasting, structural time series models and the Kalman Filter. Cambridge, New York
Junger, W. L. (2004) Semiparametric Poisson-Gamma models: a roughness penalty approach. MSc Dissertation. Rio de Janeiro, PUC-Rio, Department of Electrical Engineering.
Green, P. J., Silverman, B. W. (1994) Nonparametric Regression and Generalized Linear Models: a roughness penalty approach. Chapman and Hall, London
pgam, residuals.pgam, predict.pgam