# TCATA difference plot Plots TCATA difference curves. UTF-8 ```r tcata.diff.plot(x1 = x1, x2 = NA, n1 = 1, n2 = NA, attributes = c(), times = c(), lwd = 1, declutter = NA, get.decluttered = FALSE, emphasis = NA, alpha = 0.05, emphasis.lwd = 3, main = "", height = 8, width = 12, xlab = "Time", ylab = "Difference in citation proportion", axes.font = 1, axes.cex = 1, line.col = c(), x.increment = 5, legend.cex = 1, legend.font = 1, save.as = "") ``` ## Arguments - `x1`: matrix of difference proportions, or of counts if `n1` specified. If `mat2` specified then proportions or counts apply to first sample. Attributes are in rows, times in columns. - `x2`: matrix of proportions for second sample, or of counts if `n2` specified. - `n1`: number of observations for first sample - `n2`: number of observations for second sample - `attributes`: vector of attribute labels for row in `x1` (and `x2`) - `times`: vector of times for columns in `x1` (and `x2`) - `lwd`: Line width - `declutter`: indicator matrix with same dimensions of `x1` to suppress output - `get.decluttered`: if `TRUE` then calculates the `declutter` matrix from `get.mat.diff.sign` - `emphasis`: set to `1` to emphasize significant differences - `alpha`: significance level for entrywise test of `x1` and `x2` (if counts) - `emphasis.lwd`: line weight for emphasizing significant differences - `main`: plot title; see `plot` - `height`: plot height - `width`: plot width - `xlab`: label for x axis - `ylab`: label for y axis - `axes.font`: Font for axes labels; see `par`. - `axes.cex`: Size for axes labels. - `line.col`: line color for attribute lines - `x.increment`: increment between time labels on x axis - `legend.cex`: symbol size for legend - `legend.font`: Font for the legend; see `text`. - `save.as`: Filename to use if file will be saved. ## Examples ```r # difference between High and Low ethanol wines (sip 1) x.diff.raw <- t(syrah[seq(1, 1026, by = 6), -c(1:4)]) - t(syrah[seq(3, 1026, by = 6), -c(1:4)]) x.diff.smooth <- get.smooth(x.diff.raw, low.bound = -1, up.bound = 1) colnames(x.diff.smooth) <- colnames(x.diff.raw) <- times <- 10:180 tcata.diff.plot(x1 = x.diff.smooth, attributes = rownames(x.diff.smooth), times = times, lwd = 2, main = "Sip 1 differences: High-ethanol wine - Low-ethanol wine") # an example based on the syrah data set (truncated for efficiency) n <- 52 H1 <- t(syrah[seq(1, 126, by = 6), -c(1:4)] * n) L1 <- t(syrah[seq(3, 126, by = 6), -c(1:4)] * n) colnames(H1) <- colnames(L1) <- times <- 10:30 tcata.diff.plot(x1 = H1, x2 = L1, n1 = n, n2 = n, attributes = rownames(H1), get.decluttered = TRUE, lwd = 2) ``` ## References Castura, J.C., Antúnez, L., Giménez, A., Ares, G. (2016). Temporal check-all-that-apply (TCATA): A novel temporal sensory method for characterizing products. **Food Quality and Preference**, 47, 79-90. tools:::Rd_expr_doi("10.1016/j.foodqual.2015.06.017")

tcata.diff.plot function