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Estimate the row mean from a mtsdi object regarding a fixed number of imputed values
mtsdi
getmean(object, weighted=TRUE, mincol=1, maxconsec=3)
imputation object
If TRUE, weights returned by mnimput will be used form mean computation
TRUE
mnimput
integer for the minimun number of valid values by row
integer for the maximum number of consecutive missing values in a column
A vector of of rows mean with length n, where n is the number of observations.
n
It is useful just in case one wants row mean estimated. If log tranformation was used, mean is adjusted accordingly.
mnimput, getmean, edaprep
getmean
edaprep
# 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))) m <- getmean(i,2) # }
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