I have many data-sets, each one have many variables (Time, X1, X2,..,Xn, Y) and Time variable is continuous [0-1]. the number of observation in each data-set is not equal and not synchronized in time: for example in dataset1, Time (0, 0.15, 0.19, 0.22, ...,0.81, 0.95,1) and for a second dataset2, Time is (0.11, 0.18, 0.34, 0.53,. . ., 0.74, 0.91) etc.

Which method in R should i use to fit the model of forecasting to predict the variable Y at final Time=1 in a given data-set_n with only 3 or 4 observations Time (0.12, 0.22, 0.29, 0.38).


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