mtsdi (version 0.3.5)

predict.mtsdi: Imputed Dataset Extraction

Description

Extract imputed dataset from a mtsdi object

Usage

# S3 method for mtsdi
predict(object, ...)

Arguments

object

imputation object

…

further options passed to the generic function predict

Value

A vector of of rows mean with lenght \(n\), where \(n\) is the number of observations.

Details

If log tranformation was used, dataset is back transformed accordingly.

References

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.

See Also

mnimput, getmean, edaprep

Examples

# NOT RUN {
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)
# }