predict.mtsdi | R Documentation |
Extract imputed dataset from a mtsdi
object
## S3 method for class 'mtsdi'
predict(object, ...)
object |
imputation object |
... |
further options passed to the generic function |
If log tranformation was used, dataset is back transformed accordingly.
A vector of of rows mean with lenght n
, where n
is the number of observations.
Washington Junger wjunger@ims.uerj.br and Antonio Ponce de Leon ponce@ims.uerj.br
Junger, W.L. and Ponce de Leon, A. (2015) Imputation of Missing Data in Time Series for Air Pollutants. Atmospheric Environment, 102, 96-104.
Johnson, R., Wichern, D. (1998) Applied Multivariate Statistical Analysis. Prentice Hall.
Dempster, A., Laird, N., Rubin, D. (1977) Maximum Likelihood from Incomplete Data via the Algorithm EM. Journal of the Royal Statistical Society 39(B)), 1–38.
McLachlan, G. J., Krishnan, T. (1997) The EM algorithm and extensions. John Wiley and Sons.
Box, G., Jenkins, G., Reinsel, G. (1994) Time Series Analysis: Forecasting and Control. 3 ed. Prentice Hall.
Hastie, T. J.; Tibshirani, R. J. (1990) Generalized Additive Models. Chapman and Hall.
mnimput
, getmean
, edaprep
data(miss)
f <- ~c31+c32+c33+c34+c35
i <- mnimput(f,miss,eps=1e-3,ts=TRUE, method="spline",sp.control=list(df=c(7,7,7,7,7)))
predict(i)
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