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Hi Suppose I have a matrix (cohort are rows and years are columns) [2000] [2001] [2002] [2003] [C1] 0.01 0.03 0.02 0.09 [C2] 0.06 0.05 0.07 0.11 [C3] 0.1 0.5 0.4 0.98 [C4] 0.7 0.6 0.2 0.77 I want to extracts the diagonals to get a matrix which looks like this (C1 becomes C2 in 2002, C2 becomes C3 in 2003

Hi, I have two 3 D arrays. Both are of this form array_1<- array[n,n,k] array_2<-array[m,m,k] Lets say n=83 and m=80 Since n>m. I would like to add rows and columns to array_2 to make them equal. I want to keep the size of the third dimension fixed i.e.. k. i.e. if (nrow(array_1)>nrow(array_2)) { array_2[m:n,m:n,]<- 10^6 } But this doesn't work. I tried abind and rbind but

Hi, I am trying to fit cubic spline to a data on mortality rate by age and year (1900-2008). The data is noisy and hence I would like to smooth using spline and also extrapolate beyond 2008. Data from 1900 to 1948 are very unreliable while data from 1948 to 2008 are reliable. I would like to have a higher weight for data between 1948 to 2008. I am not sure how to do this. When I smooth data from