plot.pcrfit {qpcR} | R Documentation |
A plotting function for data of class 'pcrfit' (single curves), 'modlist' (batch curves) or 'replist' (replicate curves) displaying the data points, the fitted curve and (if desired) confidence/prediction bands/error bars on replicates. Three different plot types are available, namely plotting all curves in 2D/3D graphs or a plot matrix with one graph per curve.
## S3 method for class 'pcrfit': plot(x, fitted = TRUE, confband = c("none", "confidence", "prediction"), errbar = c("none", "sd", "se", "conf"), add = FALSE, col = NULL, level = 0.95, xlim = NULL, which = c("all", "single", "3D"), ...)
x |
an object of class 'pcrfit', 'modlist' or 'replist'. |
fitted |
should the fitted line be displayed? |
confband |
should confidence/prediction bands be displayed? See confint . |
errbar |
the type of error bar on the plot if replicates exist. See 'Examples'. |
add |
should the curve be added to an existing plot? |
col |
an optional color vector for the individual curves. Is recycled to the number of runs in x . |
level |
the confidence level used for confband or errbar . |
xlim |
a 2-element vector of the x-value (Cycles) region that should be plotted. |
which |
plots all curves in one 2D or 3D graph or many graphs with single curves. |
... |
other parameters to be passed to plot or predict . |
Uses the 'rgl' package for 3D plots. If the 'modlist' contains data that failed to fit, these are missing in the plots.
A qPCR plot.
If object
was of class 'replist', colour coding of the curves is done automatically.
Andrej-Nikolai Spiess
## single plot m1 <- pcrfit(reps, 1, 2, l5) plot(m1) ## add another plot in blue ## with 99% confidence interval m2 <- pcrfit(reps, 1, 12, l5) plot(m2, add = TRUE, col = 4, confband = "confidence", level = 0.99) ## plot a 'modlist' batch with coloring of replicates ml <- modlist(reps, 1, 2:13, model = l4) plot(ml, col = gl(3,4)) ## only the fitted curves ## and a subset of data plot(ml, type = "n", col = gl(3,4), xlim = c(10, 30)) ## plot a 'replist' rl <- replist(ml, group = gl(3, 4)) plot(rl) ## standard deviation instead of ## replicate points plot(rl, type = "n", errbar = "sd") ## 95% confidence values plot(rl, type = "n", errbar = "conf") ## plot single curves. ## good for diagnostics... plot(ml, which = "single", col = gl(3, 4)) ## 3D plots of 'modlist's or 'replist's plot(ml, which = "3D", col = gl(3, 4)) rgl.close() plot(rl, which = "3D") rgl.close()