get_eigen_spline_matrix | R Documentation |
Generate Ind x Time data.frame
for each variable using get_ind_time_matrix
and then concatenate all variables rowise. Resulting data.frame
contrain Time as columns and Individuals and Variables as rows. Pairs of Individual and Timepoint without a measurement are left as NA. If ncore!=0 the function is parallelised, however the parallelisation overhead cost is high if not required.
get_eigen_spline_matrix(inputData, ind, time, ncores = 0)
inputData |
|
ind |
Vector of subject identifier (individual) corresponding to each measurement |
time |
Vector of time corresponding to each measurement |
ncores |
(int) Number of cores to use for parallelisation. Default 0 for no parallelisation. |
data.frame
of measurements for each IND x TIME + VAR. Rows are unique Individual IDs per variable, and columns unique measurement Time. Pairs of (IND,TIME+VAR) without a measurement are left as NA.
## Not run: ## 6 measurements, 3 subjects, 3 unique time-points, 2 variables inputData <- matrix(c(1,2,3,4,5,6, 7,8,9,10,11,12), ncol=2) ind <- c('ind_1','ind_1','ind_1','ind_2','ind_2','ind_3') time <- c(0,5,10,0,10,5) get_eigen_spline_matrix(inputData, ind, time, ncores=0) # 0 5 10 # 1 1 2 3 # 2 4 NA 5 # 3 NA 6 NA # 4 7 8 9 # 5 10 NA 11 # 6 NA 12 NA ## End(Not run)
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