# Plot ridge function Plot method for the ridge and smooth terms of a `cgaim` object. If provided, also plots confidence intervals. ```r ## S3 method for class 'cgaim' plot(x, select = NULL, ci = NULL, ci.plot = c("polygon", "lines"), ci.args = list(), add = FALSE, xcenter = FALSE, xscale = FALSE, yshift = FALSE, yscale = FALSE, ...) ``` ## Arguments - `x`: A `cgaim` object. - `select`: A numeric or character vector indicating which terms to plot. - `ci`: An object returned by a call to `confint.cgaim`. If `NULL`, no confidence interval is drawn. - `ci.plot`: Whether to plot the confidence intervals as shaded areas `ci.plot = "polygon"` or as lines `ci.plot = "lines"`. - `ci.args`: Additional arguments to be passed to the function used to draw confidence interval. Either `polygon` or `lines`. - `add`: Logical. If TRUE, adds the function to the current active plot. - `xcenter, xscale`: Centering and scaling values for the x axis. See `scale`. - `yshift, yscale`: Either logical or numeric values to shift and scale the ridge functions. See details. - `...`: Additional graphical parameters for the drawn function. See `par`. ## Returns The function is called to generate plots and returns no value. ## Details The values of `yshift` and `yscale` determine how ridge functions are shifted and scaled for plotting. This can be used to display the functions over data points for instance. If numeric, a vector can be passed with one value for each plotted function. The vector is recycled if necessary. This indicate the desired mean and standard deviation of plotted ridge functions. Note that this is inverse to the parameters in `scale` (and `xcenter,xscale`). If TRUE is passed instead, functions are shifted to the intercept and scaled to their corresponding beta coefficients, placing them on the response scale. ## Examples ```r ## Simulate some data n <- 200 x1 <- rnorm(n) x2 <- rnorm(n) x3 <- rnorm(n) x4 <- rnorm(n) mu <- 4 * exp(8 * x1) / (1 + exp(8 * x1)) + exp(x3) y <- 5 + mu + rnorm(n) df1 <- data.frame(y, x1, x2, x3, x4) ## Fit a model ans <- cgaim(y ~ g(x1, x2, label = "foo") + g(x3, x4, label = "bar"), data = df1) ## Default plot method plot(ans) ## Select variable plot(ans, select = 1) # Same as plot(ans, select = "foo") ## Add confidence intervals ci <- confint(ans) plot(ans, select = 1, ci = ci) ## Change scale and location # On the response scale plot(ans, select = 1, ci = ci, yshift = TRUE, yscale = TRUE) # Arbitrary scale plot(ans, select = 1, ci = ci, yshift = 1000) ## Change look # Main line plot(ans, select = 1, ci = ci, col = 2, lwd = 3) # Confidence intervals plot(ans, select = 1, ci = ci, col = 2, lwd = 3, ci.args = list(col = adjustcolor(2, .5))) # Confidence interval type plot(ans, select = 1, ci = ci, ci.plot = "lines", col = 2, lwd = 3, ci.args = list(col = 2, lty = 4)) ## Put curves on the same plot (need to shift and scale) plot(ans, select = 1, col = 2, ylim = c(-2, 3)) plot(ans, select = 2, col = 4, add = TRUE) ``` ## See Also `cgaim` for the main fitting function and `confint.cgaim` for confidence interval computation.

plot.cgaim function