1d:T756,# Calculation of warping coefficients when applying more than one warping function successively Applying two (or more) warping function after each other can be described with one warping function of a higher warping degree. This function provides the coefficients of this higher degree warping function. ```r calc.multicoef(coef1, coef2) ``` ## Arguments - `coef1`: vector containing the warping coefficients of the first applied warping function - `coef2`: vector containing the warping coefficients of the second applied warping function ## Details This function uses Pascal's simplex to calculate the new warping coefficients. When applying three warping functions successively (first a, then b and finally c - here a, b and c are vectors of warping coefficients), first calculate the new coefficients for b and c, and afterwards the coefficients for a with these new coefficients. So the coefficients for the total warping function can be calculated via `calc.multicoef(a, calc.multicoef(b, c))`. ## Returns a vector containing the corrected warping coefficients ## See Also `calc.zerocoef` ## References Bloemberg, T.G., et al. (2010) "Improved parametric time warping for Proteomics", Chemometrics and Intelligent Laboratory Systems, 104 (1), 65 -- 74. ## Examples ```r data(gaschrom) ref <- gaschrom[1,] samp <- gaschrom[16,] coef1 <- c(100,1.1, 1e-5) coef2 <- c(25, 0.95, 3.2e-5) gaschrom.ptw <- ptw(ref, samp, init.coef = coef1, try = TRUE) ref.w <- gaschrom.ptw$reference samp.w <- gaschrom.ptw$warped.sample samp.w[is.na(samp.w)] <- 0 gaschrom.ptw2 <- ptw(ref.w, samp.w, init.coef = coef2, try = TRUE) plot(c(gaschrom.ptw2$warped.sample), type = "l") corr.coef <- calc.multicoef(coef1, coef2) gaschrom.ptw3 <- ptw(ref, samp, init.coef = corr.coef, try = TRUE) lines(c(gaschrom.ptw3$warped.sample), col = 2, lty = 2) ``` ## Author(s) Jan Gerretzen

calc.multicoef function